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Personalized safety instruction system for construction site based on internet technology
Safety Science 116 (2019) 161–169
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Personalized safety instruction system for construction site based on internet technology
T
Ning Tanga, Hao Hub, , Feng Xub, Fengfeng Zhua ⁎
a
Department of Civil Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China b Institute of Engineering Management, School of Naval Architecture, Ocean and Civil Engineering, and State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China
ARTICLE INFO
ABSTRACT
Keywords: Construction safety Construction workers Personalized safety instruction Management information system Real-time location
Safety instruction, as a critical part of safety management, plays an important role on construction sites. Unified safety training and irregular inspection are the main safety instructions methods. Considering the complex construction site and low management density, safety instructions received by workers are usually not timely and precise. To improve this situation, this paper established a real-time personalized safety instruction method which considers the different characteristics of workers and complex construction environment. A user-oriented PSIM system is developed in this paper based on GPS and cloud computing. This system could facilitate the collection of the main hazards, safety instructions to these hazards, and project information using questionnaire investigation and paper document. The collected information is classified by 5W1H method and transferred to particular workers according to their different characters, including locations, duties and working time. A case study is presented, which highlight its method for recording data, processing data, and sending personalized safety instruction, in a high-speed railway project. The results demonstrate that important construction information related to both safety and activity in field operations can be automatically processed and visualized in real-time, thus offering benefits to reducing hazards, improving safety awareness of workers, and creating a safer environment for workers effectively at a reasonable cost.
1. Introduction Despite improved technology and legislation over the past decades, the casualty rate of the construction industry is still among the highest in most countries. In China, the construction industry recorded more than 42, 500 causalities due to serious safety accidents from 2001 to 2015 (Safety, 2016). Among the complex causes of safety accidents, a lack of sufficient safety instruction is a nonnegligible factor. Construction sites are dangerous due to a large number of workers, materials, and equipment dynamic and unforeseen circumstances (Kim and Park, 2013). To improve the safety of a construction site, safety managers should give on-site construction workers safety instructions timely and make optimal decisions accordingly. However, useful safety instructions are not always accessible to workers. Helpful safety instructions rely on the cooperation of different sectors and relevant information of a specific project, including a vast number of laws, regulations, company safety policies, 2D drawings and implicit experience (Gui et al., 2017). In most cases, safety instructions are delivered by on-site
⁎
engineers, supervisors and or foremen. Effective safety instructions are not possible if the supervisors or foremen are not qualified. Even these site managers are restricted by the project managers to improve the safety level, it is difficult for them to monitor and control the entire onsite situation and give personalized, practical instructions to all workers on account of the variety of construction work and large numbers of construction workers. In short, the current safety management system has limitations concerning personalization, timeliness, and effectiveness. Fortunately, safety instruction could be improved with the help of modern technology. Many researchers have applied Internet technology to the construction industry, including construction design, site planning, risk management, safety monitoring and safety training (Zou and Lun, 2017). Sensors and visualization monitoring system (Skibniewski, 2014) and sensor-based location tracking systems such as the Global Positioning System (GPS) and Geographic Information System (GIS) have been widely used in safety monitoring (Cheng and Teizer, 2013; Wang et al., 2014; Kimmance et al., 1999; Yang et al., 2012). Safety risk
Corresponding author. E-mail addresses: [email protected] (N. Tang), [email protected] (H. Hu), [email protected] (F. Xu), [email protected] (F. Zhu).
https://doi.org/10.1016/j.ssci.2019.03.001 Received 24 October 2018; Received in revised form 25 January 2019; Accepted 1 March 2019 0925-7535/ © 2019 Elsevier Ltd. All rights reserved.
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information flow (Cheng et al., 2012; Zhou et al., 2015), safety knowledge management (Gui et al., 2017) and real-time communication (Zou and Lun, 2017; Nuntasunti and Bernold, 2006; Rozenfeld et al., 2010) have also been investigated by many researchers. However, few studies focus on personalized safety instruction on construction sites, which is vital to ensure the safety of workers in a complex and dynamic construction environment. Traditional safety instructions are unanimous to all workers and do not take into account the age, experience and other personal characteristics of workers. To improve the current situation, we developed a Personalized Safety Instruction Management (PSIM) system. The PSIM provides personalized instructions considering the features of project, the project schedule, different types of work, experience of workers, and physical condition of workers. After analyzing the current safety management system, researchers established the architecture and system function of the PSIM and explained data collection, retrieval, and processing of the system in detail. The system integrates several current IT technologies, including cloud computing, GPS and intelligent mobile technology. The collected safety data is stored and processed automatically in the cloud and could be visualized on the application built-in the smartphone of workers in real-time. The application of the PSIM system is a significant improvement upon the conventional method of safety management and makes it possible for more efficient safety monitoring on site. The rest of the paper is organized as below: Section 2 reviews the current safety instruction management and technology used in the construction industry. Section 3 develops the Personalized Safety Instruction Management System. Section 4 shows the information retrieval, collection, and processing used in the PSIM system. In Section 5, a case study and expert workshop are presented to demonstrate the effectiveness of the system. Finally, discussion and prospects are given in Section 6.
adopt virtual prototyping (VP) technology to identify critical safety accidents factors and explore management methods through modeling and simulation. However, the conclusions of these studies are always applied to general management instead of personalized management, and many risks related to personalized factors are not resolved. 2.2. Safety information management on construction site Safety information is essential for construction safety management (El-Saboni et al., 2009). Traditionally, safety information between team members relies on paper-based documents or face-to-face communication (Cheng and Teizer, 2013), which are often insufficient and informal (Hammad, 2008). With the development of information technology, practitioners started to adopt new communication tools in construction safety management and considered effective real-time site information communication to be helpful in making wise decisions (Cheng et al., 2012; Wang et al., 2018). Nuntasunti and Bernold (2006) adopted wireless technology to deliver timely information within a construction site. They proposed an integrated wireless site (IWS) concept which combined integrated equipment, tools, specialty devices, and construction personnel promises to provide real-time communication. Lee et al. (2009) and Kanan et al. (2018) use radio frequency, directional antennas, and ultrasound waves for detecting, transmitting, and reporting the risk of construction workers for managers. The safety inspection is the most common and imperative practices to enhance construction safety management. Lin et al. (2014) developed usercentered information and communications iPad application for safety inspectors, which created a personalized mobile reminding service and helped improve daily practices and management. Although more and more researchers have paid attention to the importance of safety instruction and have employed modern technology, there is no application of modern technology in practice to give effective safety instructions to workers in real-time. This paper thus integrates information analysis with on-site construction safety management and targets for developing a dynamic personalized safety instruction system for construction workers.
2. Literature review In construction sites, frequent work rotations, changing environments and concurrent activities make it difficult for effective safety management, resulting in high accident rates (Rozenfeld et al., 2010). In construction safety management, researchers take many approaches to improve the situation, among which analyzing construction information, importing location technology and giving safety instruction are discussed below.
2.3. Personalized system of instruction The personalized system of Instruction (PSI) has a long history and develops fast. PSI was first used in education and develops to an independent study method in which students take primary responsibility for their own learning (Bloom, 1956). Its main features were stressing on the written word rather than lecture, unit mastery requirement, student self-pacing, use of proctors and lectures and demonstration as motivational devices, which gave a chance to distance education and improved the educational effect greatly (Grant and Spencer, 2003). With the development of Internet technology, the content delivery of PSI became more and more comprehensive and PSI has shifted towards personalized online learning with intelligent tutoring systems (ITS) recently (Lin et al., 2014). PSI has been widely used in traffic monitoring, social activities, intelligent medical assistant monitoring, and other aspects to instruct users intelligently. Wan et al. (2014) applied situational awareness technology to monitor road vehicles and provided intelligent parking services; Gretzel (2011) summarized the impact of PSI on Tourism from the social science field. Sottilare et al. (2017) took advantage of smart glasses and pressure sensors to support adaptive instruction for military medical training in the wild. PostmaNilsenová et al. (2015) utilized automatic detection of facial movements to detect whether elderly users understood verbal medical instructions and gave special help. Researchers have also done some work to use PSI in safety management on construction site. Lin et al. (2014) designed a user-centered information and communication technology (ICT) tool to improve safety inspections. In these studies, PSI has been proved to have its great advantages in precise management and complex context, which is needed in modern construction safety
2.1. Construction safety knowledge management Construction knowledge management is an integral part of the construction industry. Specifically, safety information analysis plays a significant role and receives attention from researchers all over the world. Some researchers inductively analyzed case studies about the holistic risk level of a project and got some general conclusions. Tamošaitienė et al. (2013) employed multi-criteria decision-making methods to consider macro, mezzo and micro levels of a construction project and used TOPSIS-F method to evaluate the entire risk of the project. Abdul-Rahman et al. (2013) used Fuzzy Synthetic Analysis (FSA) to assess holistic risk based on incomplete data and vague environments. Cagno et al. (2001) have developed an algorithm to calculate operational constraint and evaluate priority index to reduce possible risk. Hallowell (2012) conducted 11 case studies of American general conductors to investigate how safety knowledge management strategies are employed, including acquisition, storage, and transfer. Saurin et al. (2002) argued that managers should make hierarchical levels of producing control to manage the onsite work and allow workers to participate in safety management. Some researchers integrated safety management information with productive on-site project work, which can be emulated by a similar construction. Ding et al. (2016) combined BIM, ontology and semantic web technology for construction risk knowledge in a BIM environment. Guo et al. (2013) 162
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management. However, there are few researchers focusing on workers' personalized safety instructions on construction site, which is important to help the large number of construction workers to reduce safety risk.
excellent safety management capabilities and crisis response capabilities. According to the investigation with two senior systems programmers and a general contractor from Company C, the high cost of installation and use is the fundamental reason why many applications are difficult to be used in the construction site (Tang, 2017). To select the appropriate architecture for the PSIM system, the following requirements have been considered: (1) reliable information storage, (2) fast computation capability and robust information processing capability, (3) real-time instruction transfer and visualization, (4) minimized physical IT capital expenditures, (5) easiness of operation. After comparing different location systems and network modes, we chose the GPS location system and Software as a Service (Saas) mode of cloud computing considering the cost and function. GPS location system is a basic function of smart phones which are almost owned by every worker in China. The position error of GPS iswithin 20 m and meets the requirements of the PSIM. Using GPS positioning embedded in mobile phones can reduce the hardware cost and training cost of PSIM system. Saas offers software that is an interface for users to communicate with the respective cloud to perform pre-programmed tasks. This service has a big advantage in flexibility and cost (Rosenberg and Mateos, 2011). The users do not need to maintain the cloud by themselves and the suppliers ensure the security and confidentiality of data, thus greatly reducing the threshold and risk of enterprise informatization. The user interface consists of two parts: a webpage and an application built into the smartphone. The webpage is used to manage and release safety instructions for managers, and the application is used to receive information. The Android operating system is selected to develop the application of PSIM because it is launched under the Open Handset Alliance. Also, most construction workers use smartphones that operate in the android system. Android system allows developers to use a customized Structured Query Language (SQL) engine to develop the PSIM mobile application, which does not require huge storage space and could receive and update data from the server. The primary system structure design and information flow of PSIM are shown in Fig. 2. Firstly, administrators input safety instructions in the system through webpages and construction workers send their personal information including name, the types of work, gender, age, work experience, history accident and location through smartphones. The information is stored and processed to produce personalized safety instructions in a cloud platform. Construction workers will then receive customized safety instructions, which could be viewed on their smartphones. Secondly, when workers encounter unexpected emergencies, they can also actively seek help from cloud platforms and administrators via the application as shown in the counter-clockwise circle. When the cloud platform receives a worker's request for help, it will report to the responsible leaders automatically and make quick instructions based on the security information stored on the cloud platform.
2.4. Location technologies on construction site Outdoor construction sites are set in dynamic environments, and there has been a frequent interaction between construction resources (workers, equipment, and materials) (Iqbal et al., 2015). To improve the safety of on-site construction operations, managers need to record accurate and reliable data of these interactions. (Kim et al., 2013). Researchers have attempted to use different technologies such as Global Positioning Systems (GPS), Radio Frequency Identification (RFID), Ultra-wideband (UWB), monitoring cameras, computer vision and machine learning technologies to get precise locations of workers. GPS is the most widely-used technology for on-site location, and its accuracy is within 20 m. Once sensors in types of equipment send signals to more than four of the 24 communication satellites, the GPS could locate and track the position of machines and workers. Compared with GPS, Radio Frequency Identification (RFID) and Ultra-wideband (UWB) are used in small construction areas, and their accuracy is within 1 m. Wang et al. (2017) used RFID to improve the efficiency of the construction supply chain by providing item-level identification and real-time information. Yang et al. (2016) and Park (2012) derived worker action recognition from pre-segmented video clips and applied action detection in longer videos to locate workers and assess their state of work. Jiang (2014) used GPS in bridge axis lofting study, and Zhu et al. (2016) used GPS to locate on-site workers and mobile equipment and predict their future positions to prevent possible collisions. Li et al. (2013) combined Global Positioning System (GPS) and Radio Frequency Identification (RFID) to monitor blind mobile tower cranes safety condition. The application of location technology improves engineering quality and reduces safety risks from the perspective of conflict between human and hazard sources. However, the safety risks caused by the unsafe actions of workers have not been well addressed. There are still few scholars who utilized location technology into workers' personal safety management, and gave personalized safety instructions based on their personal characteristics and special environment. 3. Technical strategy To provide individual onsite workers with a real-time personalized warning and reminding information, the researchers should ensure the system could get accurate locations from workers and get respond from managers in real-time. This paper adopts a user-oriented technical strategy to develop the PSIM system for the construction site. Its stages of development include system requirements, system feasibility, system implication, function analysis, system coding, and system testing and result analysis, as shown in Fig. 1. After analyzing the system requirements, the researchers adopted Internet technology, cloud computing, GPS, and smartphones to create the system. Then the system architecture and system function were established. 5W1H (Who, When, Where, Why, What and How) method is adapted to process the information, and the system is coded based on the rules of “If-Then-Else”. To test the effectiveness of the PSIM system, the authors conducted an on-site test and an expert workshop. The architecture, system function analysis, and system implementation are described in detail in the following section. The collection of safety instructions will be introduced in Section 4.
3.2. Implementation of the PSIM system As discussed in the architecture and function analysis above, the process of matching collected safety instructions with individual workers is completed in the cloud system. The personalized safety instructions shown on the smartphone application will remind workers of the potential risks involved in different work types and appropriate actions in different circumstances. In practice, users need to register the application first, so that their roles could be identified by the system. When they enter the construction zones, the application will capture and record the location of workers in real time. After data processing, the background information system will send corresponding safety instructions. The system will not start working until users reach their working areas. Fig. 3 shows the workflow of the PSIM system. When a worker carries a registered smartphone and enters the construction site, the GPS-enabled application can locate and record the worker's location information in real time. Subsequently, the
3.1. Architecture for PSIM system China Railway Lanzhou Group Company Limited (Hereafter called “Company C”) is one of the best railway construction companies in China and mainly engages in railway construction in Plateau and mountainous areas. Project managers in Company C generally have 163
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Fig. 1. User-oriented design flow chart for PSIM system.
application transmits the worker's location and personal information to the cloud platform in real time. It is assumed that at a specific time, the relationship between workers and the workplace, work content and
OLAP Database
Project data; Safety information
Administrator
safety information is a one-to-one correspondence. The cloud platform combines this information with pre-stored project information and security information in the system to generate unique security
Personalized Safety instruction via system Location safety alarm information
Safety alarm information
Safety alarm information
Manually Safety Instruction Safety alarm information Fig. 2. Information flow of PSIM execution. 164
Location
Smartphone
Personalized Safety instruction via system
Workers
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Information of Worker X (Job and characters)
Working Time (Refers to a certain working day)
Construction Schedule (Process, task and assignment)
Safety Information Database
Construction Daily Task of Worker X
Construction Drawings
The information is obtained by system processing. System information inputted by workers.
Personalized Safety Instruction
Construction Site of Worker X
The Location of Worker X
Concordant
No
System information inputted by managers. Information obtained by PSIM system automatically.
Yes Send Personalized Safety Instruction to Worker X Fig. 3. Workflow of PSIM system.
documents. Therefore, this study adopts a Brainstorm method, by which face-to-face interviews and review sessions with partner company senior engineers and managers are conducted. All the questions were semi-structured so that they were normative in form and allowed interviewees to elaborate on their answers. There was consistency in the responses, and the results could be used to generate standard safety instructions. As useful supplements, paper safety documents such as Pre-Start Meeting Record, Permit to Penetrate Request and Approval, Job Safety Analysis and Safety Incident Reporting were referenced in this study. To demonstrate the production of safety instruction, the authors use a railway construction project as an example. Overall, the output of safety instruction goes through three stages: identification of safety risk, assessment of safety risk, and safety risk response.
management information according to the 5W1H rule. Details of safety information database and personalized safety instruction will be introduced in Section 4. The daily task of a worker is determined by the worker's expertise, construction content, construction schedule, and working time. According to the types of work and contruction drawings, every worker has his specific workplace. Only after arriving at the workplace can workers carry out the work of the day and the safety guidance information can play a role. When mobile application monitors the location of workers arriving at the corresponding workplace, it triggers cell phone application. The location of workers by mobile phone application is a button that triggers the transmission of safety instruction. If the workers arrive at the position corresponding to the construction drawings, the cloud platform sends the safety instruction to the workers through the mobile application; if the worker does not reach the construction position, the mobile phone will relocate the worker again until the information is triggered at the designated location.
4.2.1. Identification of safety risk The first step is to identify safety accidents that may occur in construction projects. The identification of safety risk consists of 4 steps: firstly, breaking down construction work according to job types; secondly, allocating tasks to workers responsible to different types of work; thirdly, figuring out weak links in risk management and sources of risk involved in each job type; lastly, predicting risky events and their consequences. Making detailed schedules is indispensable work of project safety management, and Work Breakdown Structure (WBS) is a common method for detailed schedules. When making detailed schedules, experienced experts figured out weak links in risk management and sources of risk, and predicted risky events and their consequences. It is worth to note that effective safety instruction is closely related to workers' traits and weather conditions. For example, more attention should be given to inexperienced or aged workers and those who work in severe weather conditions. For example, rainwater reduces the friction of railings, and workers are prone to fall. Semi-stuctured interviews were conducted. The interview questions were divided into three sets: “What are the risky events that may happen in the project,“ “What are the triggering sources that affect the occurrence of these events (safety risk source)” and “What are the consequences of these events.” To illustrate, falling from high elevation and same level are common risky events. A possible cause is a failure of guardrail. Human injuries and asset damage may occur as consequences.
4. Information Retrieval, Collection, and Processing 4.1. Information retrieval In this paper, domain ontology and the 5W1H method are used in information retrieving. Domain ontology is a powerful tool to elucidate a set of concepts and relations and their domains in knowledge study. 5W1H is a method commonly used to describe news stories regarding six aspects: Who, When, Where, What, Why and How. Recently, this method has also been utilized to give a comprehensive analysis of information management. The author presents the conceptual model of the system using ontology theory (shown in Table 1). 4.2. Information collection and processing Safety instructions must be generated before they are imported into the system. The production of personalized safety instructions is both an essential and challenging task because they vary in different scenarios and have to be matched with individual workers. On-site safety information is always dynamic in nature, vague in language and massive in amount. The sources of the data are usually involved, including records of past accidents, construction experience, and legal 165
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Table 1 Concept Set of PSIM System. Layer of 5W1H
Concept
Description
Who
Managers
Personnel who are in charge of general projects or construction teams. The system records their types of work, expertise, experiences, ages and past accidents. People who do physical work in construction sites. The system records their types of work, expertise, experiences, ages and historical accidents.
Construction workers When
Master schedule Detailed schedule
Where
Construction drawings Map GPS location
What
Feasibility Report Construction Content Safety Manuals Technical standards
The general plan for the whole project such as task, staffing, inventory, technology, etc. A master schedule is a project work breakdown according to the construction period. Construction work should comply with construction schedule and construction schedule updates according to on-site construction work. The detailed plan for the project be constructed in each period and is usually produced on a monthly basis. A type of technical picture, which is used to present construction information and the relative position between construction items. Due to the one-to-one relationship between construction drawings and the construction projects, the system can segment working areas by construction drawings. Visual guidance is used to present an actual geographical area. In this paper, the authors use Google map for study. GPS is an abbreviation for Global Positioning System, a radio navigation system that provides users with accurate longitude, latitude, and elevation of three-dimensional position information for free. The system uses GPS to acquire exact locations of workers and then annotates the info on the map. The GPS records both the location of the project and the PSIM system users (construction site workers).
Construction experience
A feasibility study is an assessment of the practicality of a proposed project or system. General description for the project such as general design, construction function, construction principle, etc. A set of step-by-step instructions compiled by an organization to ensure the safety of workers. Established norms or requirements of the construction building, including uniform engineering or technical criteria, methods, processes, and practices. The experience summary of project officers and senior workers.
Why
Production of safety instruction
The method to produce safety instruction, including three stages: identification, assessment, and response.
How
Processing and transferring of personalized safety instruction
The methods of processing and transferring of customized safety instruction, such as locations, working time, work types and the names of workers.
4.2.2. Assessment of safety risk Qualitative risk assessment is the second stage of safety instruction production. After determined safety risk events, senior engineers and managers used a 1–5 Likert scale to assess the risk level. Affected region and magnitude of loss are two main factors. These safety risk events are divided into four levels in OSHAS18001 British Standards Institution (BSI), 2007. According to OSHAS18001, Risk = Probability × Severity. It uses a “5 × 5“ assessment method to identify and assess hazards into 4 ranks. When risk score [15, 25] the risk is very high and managers must take immediate measures. When risk score [8, 15) , the risk is urgent, and the ASAP after immediate. When risk score [5, 8) managers should make plans to resolve this risk. When risk score [1, 5) the risk is low and managers could take it for consideration. The risk rating results serve as indicators of the frequency of safety instructions sent to workers and the allocation of protective measures. When there are too many construction zones in operation, on-site managers could use the risk scale to determine which zone should be given the most attention. For example, as mentioned above, the instability of guardrail may lead to falling from high elevation or same level. Especially in high-rise building construction, it will cause serious safety accidents. After the identification of safety risk in Section 4.2.1, the experts assess the risk of instability of guardrail and mark the score of probability is 4, the score of severity is 3, and the risk score is thus 12. When risk score is 12, the risk rank of instability of guardrail is 2, which means the risk is urgent, and managers should take measures immediately. In fact, Hd cameras are usually installed in these areas to detect possible incidents.
information into the system, and transmitting it to the workers through the mobile phone application. Therefore, construction workers can receive personalized safety instructions before doing their daily work. This method effectively reduces the probability of dangerous events. Besides, according to historical safety events, the system can also assist managers in predicting possible risk events and making decisions. For the example mentioned above, the guardrail may be unstable in highrise building construction when rain. The PSIM system will remind workers to strengthen the guardrail and managers to make sure every worker wear the personal protective equipment. 5. Application of PSIM system The PSIM was applied to an 8-kilometer railway construction from May 5 to August 5, 2017 which was a part of a 13.8-km railway construction project (Hereafter called “Project R”) lead by Company C lasting for three years. There were about 120 workers involved in this 8-km railway construction during this period, and 70 workers of them were randomly selected to test the PSIM. The total cost of project implementation, including the cost of the base station, and the cost of software development and operation and maintenance. Each base station costs about $20 000, and 4 base stations are used; the development cost of the software is $50 000 for 5 years; the cost of software operation and maintenance is $1000 per month. Workers own smart phones mostly, and there is no investment for smartphones. The cost of PSIM system accounted for less than 10% of the company's safety investment. According to the construction schedule, the construction group would build No.267 - No.369 piers, and have four main work items: foundation, formworks, concrete works and maintenance. Each work item involved different types of work; carpenters, crane drivers, signal commanders, welders, and general workers should join hands to complete formworks, for example. Three researchers, four senior construction officers, and 70 construction workers participated in the field test. The researchers introduced the mechanism of PSIM system and collected feedback through interviews and the field experiment; the four construction officers, a project manager, a field supervisor, and
4.2.3. Safety risk response Safety risk response is the last stage of the production of safety instruction. In project management, there are practical response measures for most dangerous incidents, but they usually remain to be implicit knowledge of managers. Based on the analysis of risky events, scholars organize seminars and brainstorming workshops, and the senior engineers and managers involved can give a specific responses in different situations to apply tacit knowledge in practice. The researchers classified and collated the safety management information, inputting 166
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two senior on-site managers, were the main safety managers in Project R; the 70 workers had different types of work in the project. The education level of construction workers is always low and the staff turnover is always high. To test the effect of the PSIM system, 70 workers from about 120 workers were elected to do the experiment considering their education level and job stability. The 70 employees were evenly distributed into experimental group and control group according to various factors such as culture level, age, and types of work. During the operation, four people of the control group and five people of the experimental group left this construction site and finally the research group took the performance of 30 people who did not quit as the result. May 5 to August 5 was made as the experimental period. These three months is a good time for construction work for its good temperature, and the staff turnover is relatively low. The duty of workers was constructing piers, which was important and demanding. A formal safety management test was legally required on the construction site, which was issued by the ministry of transportation. The total score of the examination paper is 100 points, and the workers need more than 60 points to pass the exam. The more knowledge you have, the higher your score. The test was used by the group to reflect the knowledge of workers. The researchers collected the construction plan of the bridge hoisting, the specific task, the location of the task, the types of work for each task and the personal information of these workers from May 5th to August 5th. The collected data was sorted through the 5W1H method in the system for each worker's personal daily safety management information using the method mentioned in Section 4. Due to the minor inaccuracy of the phone's GPS technology, the system has a 30-second delay and an about-20-meter error in distance. PSIM will send information to workers when they are 100 -meter away from the workplace to ensure that workers receive instruction before reaching their workplace. This is in line with workers' habits and helps them make better preparation. For example, steel fixers received the following information: fasten the hoisting objects when using elevators; be cautioned not to fall off the guardrails; follow the rules given by signal
officers. Fig. 4. shows an example of the safety instruction sent to the fixer worker. The system was proved to function well according to preliminary results. During the experiment, there was no other difference between the two groups except for the use of PSIM. The system sent 3012 pieces of personalized safety instruction message, and the workers received 2800 pieces successfully, with a success rate of 93%. On May 5th and August 5th, 2017, the workers were tested on the safety management test. The experimental group was identified as group 1; the highest grade was 96, the lowest score was 73, the average rating was 79 on 5th May; the highest points was 100, the lowest score was 80, the average points was 84 on 5th August. The control group was identified as group 2; the highest grade was 97, the lowest score was 73, the average score was 78 on 5th May; the highest score was 95, the lowest score was 77, the average rating was 82 on 5th August. The test scores of construction workers in this experiments are shown in Fig. 5. The scores of group 1 after experiment were better than before experiment as shown in Fig. 5(a), and the scores of group 2 after experiment were better than before experiment as shown in Fig. 5(b). According to the test results and charts, both the experimental group and the control group got a higher scores with smaller variances on 5th August than on 5th May. The higher scores meant workers more comprehensive knowledge of the safety of the construction site after three months of work. The test scores of Group 1 and Group 2 were almost the same on 5th May as shown in Fig. 5(c), but the test scores of Group 1 were better than Group 2 on 5th August as shown in Fig. 5(d). It proved that the use of the application was helpful for workers to capture more safety knowledge. The safety records of project R also indicated the number of accidents in the experimental group was 15% less than that in the control group. After the field test, an expert workshop was held to evaluate the performance of PSIM on December, 20, 2017. Six main safety administrative including two managers from the client (Company C), the project manager and two senior engineers from the contractor company and one consultant engineer and six workers from the experimental group participated in the workshop. The participants were asked to
Fig. 4. Smartphone interface of PSIM APP. 167
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100
100
95
95 TEST SCORES
TEST SCORES
N. Tang, et al.
90 85 80
90 85 80 75
75
70
70 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930
1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930
WORKERS OF GROUP 1
WORKERS OF GROUP 2
Scores of Group 1 on 5th May
Scores of Group 1 on 5th August
(a)
(b)
100
100
95
95
90
90
TEST SCORES
TEST SCORES
Scores of Group 2 on 5th August
Scores of Group 2 on 5th May
85 80
85 80 75
75
70
70 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930
1 2 3 4 5 6 7 8 9 1011121314151617181920212223 24252627282930
WORKERS OF GROUP 1 AND GROUP 2
WORKERS OF GROUP 1 AND GROUP 2
Scores of Group 1 on 5th May
Scores of Group 2 on 5th May
Scores of Group 2 on 5th August
Scores of Group 1 on 5th August
(c)
(d) Fig. 5. The test scores of construction workers for safety information test.
Table 2 Survey results for PSIM system evaluation. Criteria
Avg. agreement level
1. The system is compatible with your company’s business value and need. 2. The system is a necessary supplement for existing safety instruction system. 3. The system can reduce the safety accident risk for workers. 4. The system can work well with the existing safety instruction system. 5. The system is easy to understand and use. 6. The system can improve safety instruction efficiency. 7. The workers could get more precise safety instruction more frequently. 8. The system could assist managers to give exact safety instructions easily. 9. The system can help to deal with an emergency. 10. The system helps reduce the non-standard operation of the construction site.
5.00 4.91 4.75 5.00 5.00 4.83 5.00 5.00 5.00 5.00
evaluate the effect and effectiveness of the PSIM system from 10 different perspectives shown in Table 2. A 5-point Likert scale measured the level of agreement with “1″ being “Strongly Disagree”, and “ 5 being “Strongly Agree”. The overall evaluation of the system was quite positive as shown in Table 2 (Tang, 2017) and the lowest score (Item 3) was 4.75. We believed the main reason was that the project team felt the PSIM was innovative and very useful to them. But we realize lots of efforts are still needed to improve the PSIM which will be discussed in the last section. Although PSIM still has some shortcomings, these qualitative feedback has proved the effectiveness of the system and has pointed out its research prospect. According to the experts, the system could make sure every worker get his personalized safety instruction before their work started and this would effectively decrease accident rates. By increasing the frequency of safety instruction delivers and the accuracy of the information, the system enhanced workers’ safety, especially in emergent situations. In the future, the system will be implemented entirely in more projects managed by Company C to obtain quantitative measurements of the system.
6. Concluding remarks The PSIM system has been successfully operated on the Internet platform, which integrates traditional safety management knowledge with up-to-date information technologies including cloud computing, GPS and intelligent mobile technology. Based on user-oriented principles, the architecture, the data, and information collection, retrieval, and processing for the system are determined. Employing the 5W1H method, the authors introduce the capturing process of the safety instruction knowledge base. The collected safety data is stored and processed automatically in the cloud and could be visualized on the application built-in the smartphone to function as real-time reminding and warning for workers in their daily job. The on-site test and expert workshop show PSIM is an advanced and effective system for safety instruction in the construction industry. The application of the PSIM system has changed the conventional method of safety management and make it possible of a more efficient safety monitoring and regulation on site. Undoubtedly, the construction industry and Internet technology in the future will be more interconnected, and some pioneers have started their work in this regard. Though the conceptual philosophy of PSIM 168
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system proposed in this paper is just a sign of this impact, yet its implication in managerial systems based on Internet platform cannot be underestimated. Personalized management is an important direction for safety management. The PSIM system takes into account the stable physical condition, experience, type of work, work area, task, age and of workers, and provides personalized safety instructions accordingly. However, the PSIM cannot well manage the dynamic physical conditions, such as fatigue, heart rate, blood pressure, and environmental safety conditions like the rushing cranes in real-time. Dynamic environment and stable condition interact with each other and decide the personalized safety state of workers together. The authors will make more effort to innovate the PSIM system in the aspects of real-time management in the personality information and lay a foundation for the future introduction of artificial intelligence into the construction industry.
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Acknowledgements The authors express their sincere gratitude to China Railway Lanzhou Group Company Limited (Grant ID: 17H2H22000081) for assisting in data collection and conducting on-site interviews and test. They also thank the project engineers for valuable information and useful data. Besides, the authors would like to thank Shaopei Lin, Qinruo Hu and Yue Xue for their help and support. References Abdul-Rahman, H., Wang, C., Lee, Y.L., 2013. Design and pilot run of fuzzy synthetic model (fsm) for risk evaluation in civil engineering. J. Civil Eng. Manage. 19 (2), 217–238. Bloom, B.S., 1956. Taxonomy of educational objectives: cognitive and affective domains. David McKay, New York. British Standards Institution (BSI), 2007. OHSAS 18002: Occupational health and safety management system - hands guide. British Standards Institution, London. Cagno, E., Giulio, A.D., Trucco, P., 2001. An algorithm for the implementation of safety improvement programs. Saf. Sci. 37 (1), 59–75. Cheng, E.W.L., Ryan, N., Kelly, S., 2012. Exploring the perceived influence of safety management practices on project performance in the construction industry. Saf. Sci. 50 (2), 363–369. Cheng, T., Teizer, J., 2013. Real-time resource location data collection and visualization technology for construction safety and activity monitoring applications. Autom. Constr. 34 (13), 3–15. Ding, L.Y., Zhong, B.T., Wu, S., Luo, H.B., 2016. Construction risk knowledge management in BIM using ontology and semantic web technology. Saf. Sci. 87, 202–213. El-Saboni, M., Aouad, G., Sabouni, A., 2009. Electronic communication systems effects on the success of construction projects in United Arab Emirates. Adv. Eng. Inf. 23 (1), 130–138. Grant, L., Spencer, R., 2003. The personalized system of instruction: review and applications to distance education. Int. Rev. Res. Open Distribut. Learning 4 (2). Gretzel, U., 2011. Intelligent systems in tourism. Annals Tourism Res. 38 (3), 757–779. Gui, G., Pan, H., Lin, Z., Li, Y., Yuan, Z., 2017. Data-driven support vector machine with optimization techniques for structural health monitoring and damage detection. Ksce J. Civil Eng. 21 (2), 523–534. Guo, H.L., Li, H., Li, V., 2013. Vp-based safety management in large-scale construction projects: a conceptual framework. Autom. Constr. 34 (2), 16–24. Hallowell, M.R., 2012. Safety-knowledge management in American construction organizations. J. Manage. Eng. 28 (2), 203–211. Hammad, A., 2008. Distributed augmented reality for visualizing collaborative construction tasks. J. Comput. Civil Eng. 23 (6), 418–427. Iqbal, S., Choudhry, R.M., Holschemacher, K., Ali, A., Tamošaitienė, J., 2015. Risk management in construction projects. Technol. Econ. Develop. Econ. 21 (1), 65–78.
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Personalized safety instruction system for construction site based on internet technology
T
Ning Tanga, Hao Hub, , Feng Xub, Fengfeng Zhua ⁎
a
Department of Civil Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China b Institute of Engineering Management, School of Naval Architecture, Ocean and Civil Engineering, and State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China
ARTICLE INFO
ABSTRACT
Keywords: Construction safety Construction workers Personalized safety instruction Management information system Real-time location
Safety instruction, as a critical part of safety management, plays an important role on construction sites. Unified safety training and irregular inspection are the main safety instructions methods. Considering the complex construction site and low management density, safety instructions received by workers are usually not timely and precise. To improve this situation, this paper established a real-time personalized safety instruction method which considers the different characteristics of workers and complex construction environment. A user-oriented PSIM system is developed in this paper based on GPS and cloud computing. This system could facilitate the collection of the main hazards, safety instructions to these hazards, and project information using questionnaire investigation and paper document. The collected information is classified by 5W1H method and transferred to particular workers according to their different characters, including locations, duties and working time. A case study is presented, which highlight its method for recording data, processing data, and sending personalized safety instruction, in a high-speed railway project. The results demonstrate that important construction information related to both safety and activity in field operations can be automatically processed and visualized in real-time, thus offering benefits to reducing hazards, improving safety awareness of workers, and creating a safer environment for workers effectively at a reasonable cost.
1. Introduction Despite improved technology and legislation over the past decades, the casualty rate of the construction industry is still among the highest in most countries. In China, the construction industry recorded more than 42, 500 causalities due to serious safety accidents from 2001 to 2015 (Safety, 2016). Among the complex causes of safety accidents, a lack of sufficient safety instruction is a nonnegligible factor. Construction sites are dangerous due to a large number of workers, materials, and equipment dynamic and unforeseen circumstances (Kim and Park, 2013). To improve the safety of a construction site, safety managers should give on-site construction workers safety instructions timely and make optimal decisions accordingly. However, useful safety instructions are not always accessible to workers. Helpful safety instructions rely on the cooperation of different sectors and relevant information of a specific project, including a vast number of laws, regulations, company safety policies, 2D drawings and implicit experience (Gui et al., 2017). In most cases, safety instructions are delivered by on-site
⁎
engineers, supervisors and or foremen. Effective safety instructions are not possible if the supervisors or foremen are not qualified. Even these site managers are restricted by the project managers to improve the safety level, it is difficult for them to monitor and control the entire onsite situation and give personalized, practical instructions to all workers on account of the variety of construction work and large numbers of construction workers. In short, the current safety management system has limitations concerning personalization, timeliness, and effectiveness. Fortunately, safety instruction could be improved with the help of modern technology. Many researchers have applied Internet technology to the construction industry, including construction design, site planning, risk management, safety monitoring and safety training (Zou and Lun, 2017). Sensors and visualization monitoring system (Skibniewski, 2014) and sensor-based location tracking systems such as the Global Positioning System (GPS) and Geographic Information System (GIS) have been widely used in safety monitoring (Cheng and Teizer, 2013; Wang et al., 2014; Kimmance et al., 1999; Yang et al., 2012). Safety risk
Corresponding author. E-mail addresses: [email protected] (N. Tang), [email protected] (H. Hu), [email protected] (F. Xu), [email protected] (F. Zhu).
https://doi.org/10.1016/j.ssci.2019.03.001 Received 24 October 2018; Received in revised form 25 January 2019; Accepted 1 March 2019 0925-7535/ © 2019 Elsevier Ltd. All rights reserved.
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information flow (Cheng et al., 2012; Zhou et al., 2015), safety knowledge management (Gui et al., 2017) and real-time communication (Zou and Lun, 2017; Nuntasunti and Bernold, 2006; Rozenfeld et al., 2010) have also been investigated by many researchers. However, few studies focus on personalized safety instruction on construction sites, which is vital to ensure the safety of workers in a complex and dynamic construction environment. Traditional safety instructions are unanimous to all workers and do not take into account the age, experience and other personal characteristics of workers. To improve the current situation, we developed a Personalized Safety Instruction Management (PSIM) system. The PSIM provides personalized instructions considering the features of project, the project schedule, different types of work, experience of workers, and physical condition of workers. After analyzing the current safety management system, researchers established the architecture and system function of the PSIM and explained data collection, retrieval, and processing of the system in detail. The system integrates several current IT technologies, including cloud computing, GPS and intelligent mobile technology. The collected safety data is stored and processed automatically in the cloud and could be visualized on the application built-in the smartphone of workers in real-time. The application of the PSIM system is a significant improvement upon the conventional method of safety management and makes it possible for more efficient safety monitoring on site. The rest of the paper is organized as below: Section 2 reviews the current safety instruction management and technology used in the construction industry. Section 3 develops the Personalized Safety Instruction Management System. Section 4 shows the information retrieval, collection, and processing used in the PSIM system. In Section 5, a case study and expert workshop are presented to demonstrate the effectiveness of the system. Finally, discussion and prospects are given in Section 6.
adopt virtual prototyping (VP) technology to identify critical safety accidents factors and explore management methods through modeling and simulation. However, the conclusions of these studies are always applied to general management instead of personalized management, and many risks related to personalized factors are not resolved. 2.2. Safety information management on construction site Safety information is essential for construction safety management (El-Saboni et al., 2009). Traditionally, safety information between team members relies on paper-based documents or face-to-face communication (Cheng and Teizer, 2013), which are often insufficient and informal (Hammad, 2008). With the development of information technology, practitioners started to adopt new communication tools in construction safety management and considered effective real-time site information communication to be helpful in making wise decisions (Cheng et al., 2012; Wang et al., 2018). Nuntasunti and Bernold (2006) adopted wireless technology to deliver timely information within a construction site. They proposed an integrated wireless site (IWS) concept which combined integrated equipment, tools, specialty devices, and construction personnel promises to provide real-time communication. Lee et al. (2009) and Kanan et al. (2018) use radio frequency, directional antennas, and ultrasound waves for detecting, transmitting, and reporting the risk of construction workers for managers. The safety inspection is the most common and imperative practices to enhance construction safety management. Lin et al. (2014) developed usercentered information and communications iPad application for safety inspectors, which created a personalized mobile reminding service and helped improve daily practices and management. Although more and more researchers have paid attention to the importance of safety instruction and have employed modern technology, there is no application of modern technology in practice to give effective safety instructions to workers in real-time. This paper thus integrates information analysis with on-site construction safety management and targets for developing a dynamic personalized safety instruction system for construction workers.
2. Literature review In construction sites, frequent work rotations, changing environments and concurrent activities make it difficult for effective safety management, resulting in high accident rates (Rozenfeld et al., 2010). In construction safety management, researchers take many approaches to improve the situation, among which analyzing construction information, importing location technology and giving safety instruction are discussed below.
2.3. Personalized system of instruction The personalized system of Instruction (PSI) has a long history and develops fast. PSI was first used in education and develops to an independent study method in which students take primary responsibility for their own learning (Bloom, 1956). Its main features were stressing on the written word rather than lecture, unit mastery requirement, student self-pacing, use of proctors and lectures and demonstration as motivational devices, which gave a chance to distance education and improved the educational effect greatly (Grant and Spencer, 2003). With the development of Internet technology, the content delivery of PSI became more and more comprehensive and PSI has shifted towards personalized online learning with intelligent tutoring systems (ITS) recently (Lin et al., 2014). PSI has been widely used in traffic monitoring, social activities, intelligent medical assistant monitoring, and other aspects to instruct users intelligently. Wan et al. (2014) applied situational awareness technology to monitor road vehicles and provided intelligent parking services; Gretzel (2011) summarized the impact of PSI on Tourism from the social science field. Sottilare et al. (2017) took advantage of smart glasses and pressure sensors to support adaptive instruction for military medical training in the wild. PostmaNilsenová et al. (2015) utilized automatic detection of facial movements to detect whether elderly users understood verbal medical instructions and gave special help. Researchers have also done some work to use PSI in safety management on construction site. Lin et al. (2014) designed a user-centered information and communication technology (ICT) tool to improve safety inspections. In these studies, PSI has been proved to have its great advantages in precise management and complex context, which is needed in modern construction safety
2.1. Construction safety knowledge management Construction knowledge management is an integral part of the construction industry. Specifically, safety information analysis plays a significant role and receives attention from researchers all over the world. Some researchers inductively analyzed case studies about the holistic risk level of a project and got some general conclusions. Tamošaitienė et al. (2013) employed multi-criteria decision-making methods to consider macro, mezzo and micro levels of a construction project and used TOPSIS-F method to evaluate the entire risk of the project. Abdul-Rahman et al. (2013) used Fuzzy Synthetic Analysis (FSA) to assess holistic risk based on incomplete data and vague environments. Cagno et al. (2001) have developed an algorithm to calculate operational constraint and evaluate priority index to reduce possible risk. Hallowell (2012) conducted 11 case studies of American general conductors to investigate how safety knowledge management strategies are employed, including acquisition, storage, and transfer. Saurin et al. (2002) argued that managers should make hierarchical levels of producing control to manage the onsite work and allow workers to participate in safety management. Some researchers integrated safety management information with productive on-site project work, which can be emulated by a similar construction. Ding et al. (2016) combined BIM, ontology and semantic web technology for construction risk knowledge in a BIM environment. Guo et al. (2013) 162
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management. However, there are few researchers focusing on workers' personalized safety instructions on construction site, which is important to help the large number of construction workers to reduce safety risk.
excellent safety management capabilities and crisis response capabilities. According to the investigation with two senior systems programmers and a general contractor from Company C, the high cost of installation and use is the fundamental reason why many applications are difficult to be used in the construction site (Tang, 2017). To select the appropriate architecture for the PSIM system, the following requirements have been considered: (1) reliable information storage, (2) fast computation capability and robust information processing capability, (3) real-time instruction transfer and visualization, (4) minimized physical IT capital expenditures, (5) easiness of operation. After comparing different location systems and network modes, we chose the GPS location system and Software as a Service (Saas) mode of cloud computing considering the cost and function. GPS location system is a basic function of smart phones which are almost owned by every worker in China. The position error of GPS iswithin 20 m and meets the requirements of the PSIM. Using GPS positioning embedded in mobile phones can reduce the hardware cost and training cost of PSIM system. Saas offers software that is an interface for users to communicate with the respective cloud to perform pre-programmed tasks. This service has a big advantage in flexibility and cost (Rosenberg and Mateos, 2011). The users do not need to maintain the cloud by themselves and the suppliers ensure the security and confidentiality of data, thus greatly reducing the threshold and risk of enterprise informatization. The user interface consists of two parts: a webpage and an application built into the smartphone. The webpage is used to manage and release safety instructions for managers, and the application is used to receive information. The Android operating system is selected to develop the application of PSIM because it is launched under the Open Handset Alliance. Also, most construction workers use smartphones that operate in the android system. Android system allows developers to use a customized Structured Query Language (SQL) engine to develop the PSIM mobile application, which does not require huge storage space and could receive and update data from the server. The primary system structure design and information flow of PSIM are shown in Fig. 2. Firstly, administrators input safety instructions in the system through webpages and construction workers send their personal information including name, the types of work, gender, age, work experience, history accident and location through smartphones. The information is stored and processed to produce personalized safety instructions in a cloud platform. Construction workers will then receive customized safety instructions, which could be viewed on their smartphones. Secondly, when workers encounter unexpected emergencies, they can also actively seek help from cloud platforms and administrators via the application as shown in the counter-clockwise circle. When the cloud platform receives a worker's request for help, it will report to the responsible leaders automatically and make quick instructions based on the security information stored on the cloud platform.
2.4. Location technologies on construction site Outdoor construction sites are set in dynamic environments, and there has been a frequent interaction between construction resources (workers, equipment, and materials) (Iqbal et al., 2015). To improve the safety of on-site construction operations, managers need to record accurate and reliable data of these interactions. (Kim et al., 2013). Researchers have attempted to use different technologies such as Global Positioning Systems (GPS), Radio Frequency Identification (RFID), Ultra-wideband (UWB), monitoring cameras, computer vision and machine learning technologies to get precise locations of workers. GPS is the most widely-used technology for on-site location, and its accuracy is within 20 m. Once sensors in types of equipment send signals to more than four of the 24 communication satellites, the GPS could locate and track the position of machines and workers. Compared with GPS, Radio Frequency Identification (RFID) and Ultra-wideband (UWB) are used in small construction areas, and their accuracy is within 1 m. Wang et al. (2017) used RFID to improve the efficiency of the construction supply chain by providing item-level identification and real-time information. Yang et al. (2016) and Park (2012) derived worker action recognition from pre-segmented video clips and applied action detection in longer videos to locate workers and assess their state of work. Jiang (2014) used GPS in bridge axis lofting study, and Zhu et al. (2016) used GPS to locate on-site workers and mobile equipment and predict their future positions to prevent possible collisions. Li et al. (2013) combined Global Positioning System (GPS) and Radio Frequency Identification (RFID) to monitor blind mobile tower cranes safety condition. The application of location technology improves engineering quality and reduces safety risks from the perspective of conflict between human and hazard sources. However, the safety risks caused by the unsafe actions of workers have not been well addressed. There are still few scholars who utilized location technology into workers' personal safety management, and gave personalized safety instructions based on their personal characteristics and special environment. 3. Technical strategy To provide individual onsite workers with a real-time personalized warning and reminding information, the researchers should ensure the system could get accurate locations from workers and get respond from managers in real-time. This paper adopts a user-oriented technical strategy to develop the PSIM system for the construction site. Its stages of development include system requirements, system feasibility, system implication, function analysis, system coding, and system testing and result analysis, as shown in Fig. 1. After analyzing the system requirements, the researchers adopted Internet technology, cloud computing, GPS, and smartphones to create the system. Then the system architecture and system function were established. 5W1H (Who, When, Where, Why, What and How) method is adapted to process the information, and the system is coded based on the rules of “If-Then-Else”. To test the effectiveness of the PSIM system, the authors conducted an on-site test and an expert workshop. The architecture, system function analysis, and system implementation are described in detail in the following section. The collection of safety instructions will be introduced in Section 4.
3.2. Implementation of the PSIM system As discussed in the architecture and function analysis above, the process of matching collected safety instructions with individual workers is completed in the cloud system. The personalized safety instructions shown on the smartphone application will remind workers of the potential risks involved in different work types and appropriate actions in different circumstances. In practice, users need to register the application first, so that their roles could be identified by the system. When they enter the construction zones, the application will capture and record the location of workers in real time. After data processing, the background information system will send corresponding safety instructions. The system will not start working until users reach their working areas. Fig. 3 shows the workflow of the PSIM system. When a worker carries a registered smartphone and enters the construction site, the GPS-enabled application can locate and record the worker's location information in real time. Subsequently, the
3.1. Architecture for PSIM system China Railway Lanzhou Group Company Limited (Hereafter called “Company C”) is one of the best railway construction companies in China and mainly engages in railway construction in Plateau and mountainous areas. Project managers in Company C generally have 163
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Fig. 1. User-oriented design flow chart for PSIM system.
application transmits the worker's location and personal information to the cloud platform in real time. It is assumed that at a specific time, the relationship between workers and the workplace, work content and
OLAP Database
Project data; Safety information
Administrator
safety information is a one-to-one correspondence. The cloud platform combines this information with pre-stored project information and security information in the system to generate unique security
Personalized Safety instruction via system Location safety alarm information
Safety alarm information
Safety alarm information
Manually Safety Instruction Safety alarm information Fig. 2. Information flow of PSIM execution. 164
Location
Smartphone
Personalized Safety instruction via system
Workers
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Information of Worker X (Job and characters)
Working Time (Refers to a certain working day)
Construction Schedule (Process, task and assignment)
Safety Information Database
Construction Daily Task of Worker X
Construction Drawings
The information is obtained by system processing. System information inputted by workers.
Personalized Safety Instruction
Construction Site of Worker X
The Location of Worker X
Concordant
No
System information inputted by managers. Information obtained by PSIM system automatically.
Yes Send Personalized Safety Instruction to Worker X Fig. 3. Workflow of PSIM system.
documents. Therefore, this study adopts a Brainstorm method, by which face-to-face interviews and review sessions with partner company senior engineers and managers are conducted. All the questions were semi-structured so that they were normative in form and allowed interviewees to elaborate on their answers. There was consistency in the responses, and the results could be used to generate standard safety instructions. As useful supplements, paper safety documents such as Pre-Start Meeting Record, Permit to Penetrate Request and Approval, Job Safety Analysis and Safety Incident Reporting were referenced in this study. To demonstrate the production of safety instruction, the authors use a railway construction project as an example. Overall, the output of safety instruction goes through three stages: identification of safety risk, assessment of safety risk, and safety risk response.
management information according to the 5W1H rule. Details of safety information database and personalized safety instruction will be introduced in Section 4. The daily task of a worker is determined by the worker's expertise, construction content, construction schedule, and working time. According to the types of work and contruction drawings, every worker has his specific workplace. Only after arriving at the workplace can workers carry out the work of the day and the safety guidance information can play a role. When mobile application monitors the location of workers arriving at the corresponding workplace, it triggers cell phone application. The location of workers by mobile phone application is a button that triggers the transmission of safety instruction. If the workers arrive at the position corresponding to the construction drawings, the cloud platform sends the safety instruction to the workers through the mobile application; if the worker does not reach the construction position, the mobile phone will relocate the worker again until the information is triggered at the designated location.
4.2.1. Identification of safety risk The first step is to identify safety accidents that may occur in construction projects. The identification of safety risk consists of 4 steps: firstly, breaking down construction work according to job types; secondly, allocating tasks to workers responsible to different types of work; thirdly, figuring out weak links in risk management and sources of risk involved in each job type; lastly, predicting risky events and their consequences. Making detailed schedules is indispensable work of project safety management, and Work Breakdown Structure (WBS) is a common method for detailed schedules. When making detailed schedules, experienced experts figured out weak links in risk management and sources of risk, and predicted risky events and their consequences. It is worth to note that effective safety instruction is closely related to workers' traits and weather conditions. For example, more attention should be given to inexperienced or aged workers and those who work in severe weather conditions. For example, rainwater reduces the friction of railings, and workers are prone to fall. Semi-stuctured interviews were conducted. The interview questions were divided into three sets: “What are the risky events that may happen in the project,“ “What are the triggering sources that affect the occurrence of these events (safety risk source)” and “What are the consequences of these events.” To illustrate, falling from high elevation and same level are common risky events. A possible cause is a failure of guardrail. Human injuries and asset damage may occur as consequences.
4. Information Retrieval, Collection, and Processing 4.1. Information retrieval In this paper, domain ontology and the 5W1H method are used in information retrieving. Domain ontology is a powerful tool to elucidate a set of concepts and relations and their domains in knowledge study. 5W1H is a method commonly used to describe news stories regarding six aspects: Who, When, Where, What, Why and How. Recently, this method has also been utilized to give a comprehensive analysis of information management. The author presents the conceptual model of the system using ontology theory (shown in Table 1). 4.2. Information collection and processing Safety instructions must be generated before they are imported into the system. The production of personalized safety instructions is both an essential and challenging task because they vary in different scenarios and have to be matched with individual workers. On-site safety information is always dynamic in nature, vague in language and massive in amount. The sources of the data are usually involved, including records of past accidents, construction experience, and legal 165
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Table 1 Concept Set of PSIM System. Layer of 5W1H
Concept
Description
Who
Managers
Personnel who are in charge of general projects or construction teams. The system records their types of work, expertise, experiences, ages and past accidents. People who do physical work in construction sites. The system records their types of work, expertise, experiences, ages and historical accidents.
Construction workers When
Master schedule Detailed schedule
Where
Construction drawings Map GPS location
What
Feasibility Report Construction Content Safety Manuals Technical standards
The general plan for the whole project such as task, staffing, inventory, technology, etc. A master schedule is a project work breakdown according to the construction period. Construction work should comply with construction schedule and construction schedule updates according to on-site construction work. The detailed plan for the project be constructed in each period and is usually produced on a monthly basis. A type of technical picture, which is used to present construction information and the relative position between construction items. Due to the one-to-one relationship between construction drawings and the construction projects, the system can segment working areas by construction drawings. Visual guidance is used to present an actual geographical area. In this paper, the authors use Google map for study. GPS is an abbreviation for Global Positioning System, a radio navigation system that provides users with accurate longitude, latitude, and elevation of three-dimensional position information for free. The system uses GPS to acquire exact locations of workers and then annotates the info on the map. The GPS records both the location of the project and the PSIM system users (construction site workers).
Construction experience
A feasibility study is an assessment of the practicality of a proposed project or system. General description for the project such as general design, construction function, construction principle, etc. A set of step-by-step instructions compiled by an organization to ensure the safety of workers. Established norms or requirements of the construction building, including uniform engineering or technical criteria, methods, processes, and practices. The experience summary of project officers and senior workers.
Why
Production of safety instruction
The method to produce safety instruction, including three stages: identification, assessment, and response.
How
Processing and transferring of personalized safety instruction
The methods of processing and transferring of customized safety instruction, such as locations, working time, work types and the names of workers.
4.2.2. Assessment of safety risk Qualitative risk assessment is the second stage of safety instruction production. After determined safety risk events, senior engineers and managers used a 1–5 Likert scale to assess the risk level. Affected region and magnitude of loss are two main factors. These safety risk events are divided into four levels in OSHAS18001 British Standards Institution (BSI), 2007. According to OSHAS18001, Risk = Probability × Severity. It uses a “5 × 5“ assessment method to identify and assess hazards into 4 ranks. When risk score [15, 25] the risk is very high and managers must take immediate measures. When risk score [8, 15) , the risk is urgent, and the ASAP after immediate. When risk score [5, 8) managers should make plans to resolve this risk. When risk score [1, 5) the risk is low and managers could take it for consideration. The risk rating results serve as indicators of the frequency of safety instructions sent to workers and the allocation of protective measures. When there are too many construction zones in operation, on-site managers could use the risk scale to determine which zone should be given the most attention. For example, as mentioned above, the instability of guardrail may lead to falling from high elevation or same level. Especially in high-rise building construction, it will cause serious safety accidents. After the identification of safety risk in Section 4.2.1, the experts assess the risk of instability of guardrail and mark the score of probability is 4, the score of severity is 3, and the risk score is thus 12. When risk score is 12, the risk rank of instability of guardrail is 2, which means the risk is urgent, and managers should take measures immediately. In fact, Hd cameras are usually installed in these areas to detect possible incidents.
information into the system, and transmitting it to the workers through the mobile phone application. Therefore, construction workers can receive personalized safety instructions before doing their daily work. This method effectively reduces the probability of dangerous events. Besides, according to historical safety events, the system can also assist managers in predicting possible risk events and making decisions. For the example mentioned above, the guardrail may be unstable in highrise building construction when rain. The PSIM system will remind workers to strengthen the guardrail and managers to make sure every worker wear the personal protective equipment. 5. Application of PSIM system The PSIM was applied to an 8-kilometer railway construction from May 5 to August 5, 2017 which was a part of a 13.8-km railway construction project (Hereafter called “Project R”) lead by Company C lasting for three years. There were about 120 workers involved in this 8-km railway construction during this period, and 70 workers of them were randomly selected to test the PSIM. The total cost of project implementation, including the cost of the base station, and the cost of software development and operation and maintenance. Each base station costs about $20 000, and 4 base stations are used; the development cost of the software is $50 000 for 5 years; the cost of software operation and maintenance is $1000 per month. Workers own smart phones mostly, and there is no investment for smartphones. The cost of PSIM system accounted for less than 10% of the company's safety investment. According to the construction schedule, the construction group would build No.267 - No.369 piers, and have four main work items: foundation, formworks, concrete works and maintenance. Each work item involved different types of work; carpenters, crane drivers, signal commanders, welders, and general workers should join hands to complete formworks, for example. Three researchers, four senior construction officers, and 70 construction workers participated in the field test. The researchers introduced the mechanism of PSIM system and collected feedback through interviews and the field experiment; the four construction officers, a project manager, a field supervisor, and
4.2.3. Safety risk response Safety risk response is the last stage of the production of safety instruction. In project management, there are practical response measures for most dangerous incidents, but they usually remain to be implicit knowledge of managers. Based on the analysis of risky events, scholars organize seminars and brainstorming workshops, and the senior engineers and managers involved can give a specific responses in different situations to apply tacit knowledge in practice. The researchers classified and collated the safety management information, inputting 166
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two senior on-site managers, were the main safety managers in Project R; the 70 workers had different types of work in the project. The education level of construction workers is always low and the staff turnover is always high. To test the effect of the PSIM system, 70 workers from about 120 workers were elected to do the experiment considering their education level and job stability. The 70 employees were evenly distributed into experimental group and control group according to various factors such as culture level, age, and types of work. During the operation, four people of the control group and five people of the experimental group left this construction site and finally the research group took the performance of 30 people who did not quit as the result. May 5 to August 5 was made as the experimental period. These three months is a good time for construction work for its good temperature, and the staff turnover is relatively low. The duty of workers was constructing piers, which was important and demanding. A formal safety management test was legally required on the construction site, which was issued by the ministry of transportation. The total score of the examination paper is 100 points, and the workers need more than 60 points to pass the exam. The more knowledge you have, the higher your score. The test was used by the group to reflect the knowledge of workers. The researchers collected the construction plan of the bridge hoisting, the specific task, the location of the task, the types of work for each task and the personal information of these workers from May 5th to August 5th. The collected data was sorted through the 5W1H method in the system for each worker's personal daily safety management information using the method mentioned in Section 4. Due to the minor inaccuracy of the phone's GPS technology, the system has a 30-second delay and an about-20-meter error in distance. PSIM will send information to workers when they are 100 -meter away from the workplace to ensure that workers receive instruction before reaching their workplace. This is in line with workers' habits and helps them make better preparation. For example, steel fixers received the following information: fasten the hoisting objects when using elevators; be cautioned not to fall off the guardrails; follow the rules given by signal
officers. Fig. 4. shows an example of the safety instruction sent to the fixer worker. The system was proved to function well according to preliminary results. During the experiment, there was no other difference between the two groups except for the use of PSIM. The system sent 3012 pieces of personalized safety instruction message, and the workers received 2800 pieces successfully, with a success rate of 93%. On May 5th and August 5th, 2017, the workers were tested on the safety management test. The experimental group was identified as group 1; the highest grade was 96, the lowest score was 73, the average rating was 79 on 5th May; the highest points was 100, the lowest score was 80, the average points was 84 on 5th August. The control group was identified as group 2; the highest grade was 97, the lowest score was 73, the average score was 78 on 5th May; the highest score was 95, the lowest score was 77, the average rating was 82 on 5th August. The test scores of construction workers in this experiments are shown in Fig. 5. The scores of group 1 after experiment were better than before experiment as shown in Fig. 5(a), and the scores of group 2 after experiment were better than before experiment as shown in Fig. 5(b). According to the test results and charts, both the experimental group and the control group got a higher scores with smaller variances on 5th August than on 5th May. The higher scores meant workers more comprehensive knowledge of the safety of the construction site after three months of work. The test scores of Group 1 and Group 2 were almost the same on 5th May as shown in Fig. 5(c), but the test scores of Group 1 were better than Group 2 on 5th August as shown in Fig. 5(d). It proved that the use of the application was helpful for workers to capture more safety knowledge. The safety records of project R also indicated the number of accidents in the experimental group was 15% less than that in the control group. After the field test, an expert workshop was held to evaluate the performance of PSIM on December, 20, 2017. Six main safety administrative including two managers from the client (Company C), the project manager and two senior engineers from the contractor company and one consultant engineer and six workers from the experimental group participated in the workshop. The participants were asked to
Fig. 4. Smartphone interface of PSIM APP. 167
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100
100
95
95 TEST SCORES
TEST SCORES
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90 85 80
90 85 80 75
75
70
70 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930
1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930
WORKERS OF GROUP 1
WORKERS OF GROUP 2
Scores of Group 1 on 5th May
Scores of Group 1 on 5th August
(a)
(b)
100
100
95
95
90
90
TEST SCORES
TEST SCORES
Scores of Group 2 on 5th August
Scores of Group 2 on 5th May
85 80
85 80 75
75
70
70 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930
1 2 3 4 5 6 7 8 9 1011121314151617181920212223 24252627282930
WORKERS OF GROUP 1 AND GROUP 2
WORKERS OF GROUP 1 AND GROUP 2
Scores of Group 1 on 5th May
Scores of Group 2 on 5th May
Scores of Group 2 on 5th August
Scores of Group 1 on 5th August
(c)
(d) Fig. 5. The test scores of construction workers for safety information test.
Table 2 Survey results for PSIM system evaluation. Criteria
Avg. agreement level
1. The system is compatible with your company’s business value and need. 2. The system is a necessary supplement for existing safety instruction system. 3. The system can reduce the safety accident risk for workers. 4. The system can work well with the existing safety instruction system. 5. The system is easy to understand and use. 6. The system can improve safety instruction efficiency. 7. The workers could get more precise safety instruction more frequently. 8. The system could assist managers to give exact safety instructions easily. 9. The system can help to deal with an emergency. 10. The system helps reduce the non-standard operation of the construction site.
5.00 4.91 4.75 5.00 5.00 4.83 5.00 5.00 5.00 5.00
evaluate the effect and effectiveness of the PSIM system from 10 different perspectives shown in Table 2. A 5-point Likert scale measured the level of agreement with “1″ being “Strongly Disagree”, and “ 5 being “Strongly Agree”. The overall evaluation of the system was quite positive as shown in Table 2 (Tang, 2017) and the lowest score (Item 3) was 4.75. We believed the main reason was that the project team felt the PSIM was innovative and very useful to them. But we realize lots of efforts are still needed to improve the PSIM which will be discussed in the last section. Although PSIM still has some shortcomings, these qualitative feedback has proved the effectiveness of the system and has pointed out its research prospect. According to the experts, the system could make sure every worker get his personalized safety instruction before their work started and this would effectively decrease accident rates. By increasing the frequency of safety instruction delivers and the accuracy of the information, the system enhanced workers’ safety, especially in emergent situations. In the future, the system will be implemented entirely in more projects managed by Company C to obtain quantitative measurements of the system.
6. Concluding remarks The PSIM system has been successfully operated on the Internet platform, which integrates traditional safety management knowledge with up-to-date information technologies including cloud computing, GPS and intelligent mobile technology. Based on user-oriented principles, the architecture, the data, and information collection, retrieval, and processing for the system are determined. Employing the 5W1H method, the authors introduce the capturing process of the safety instruction knowledge base. The collected safety data is stored and processed automatically in the cloud and could be visualized on the application built-in the smartphone to function as real-time reminding and warning for workers in their daily job. The on-site test and expert workshop show PSIM is an advanced and effective system for safety instruction in the construction industry. The application of the PSIM system has changed the conventional method of safety management and make it possible of a more efficient safety monitoring and regulation on site. Undoubtedly, the construction industry and Internet technology in the future will be more interconnected, and some pioneers have started their work in this regard. Though the conceptual philosophy of PSIM 168
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system proposed in this paper is just a sign of this impact, yet its implication in managerial systems based on Internet platform cannot be underestimated. Personalized management is an important direction for safety management. The PSIM system takes into account the stable physical condition, experience, type of work, work area, task, age and of workers, and provides personalized safety instructions accordingly. However, the PSIM cannot well manage the dynamic physical conditions, such as fatigue, heart rate, blood pressure, and environmental safety conditions like the rushing cranes in real-time. Dynamic environment and stable condition interact with each other and decide the personalized safety state of workers together. The authors will make more effort to innovate the PSIM system in the aspects of real-time management in the personality information and lay a foundation for the future introduction of artificial intelligence into the construction industry.
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