A Multiagent Geosimulation and IoT-based Framework for Safety Monitoring in Complex Dynamic Spatial Environments

Haddad, Hedi; Bouyahia, Zied; Chaudhry, Shafique Ahmad

doi:10.1016/j.procs.2019.04.071

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…Safety control is a significant issue in complex spatial environments such as airports and ports. IoT can help the geosimulation process to simulate the environment and assess workers' safety [38]. Since construction job sites are classified as high-risk work environments, [39] utilize an IoT architecture and propose an autonomous system for hazard recognition and sending safety notifications to site labors.…”

Section: Iot For Construction Safetymentioning

confidence: 99%

Leading Indicators—A Conceptual IoT-Based Framework to Produce Active Leading Indicators for Construction Safety

Costin

Wehle

Adibfar

2019

Safety

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Active leading indicators (ALIs) have the potential to identify safety hazards and prompt immediate actions to prevent incidents. Currently, there is a major gap in research that incorporates a fully automated ALI system because implementation has been hindered by a lack of established industry thresholds of measurable performance that would trigger an actionable response. Therefore, this paper addresses this gap by presenting a new method that utilizes the Internet of Things (IoT) to collect quantifiable data which can trigger an actionable response in real time based on established thresholds. This novel method integrates the Construction Industry Institute (CII) active leading indicator framework with a prototype IoT-based system. Significantly, the ALI provides the physical–virtual feedback loop, which is an essential aspect of the IoT system because it provides real-time feedback to both the users and systems. This paper also identifies potential inputs to the ALI framework from emerging IoT-enabled systems. A case study was presented to initially validate the IoT-based ALI framework. Bluetooth-enabled heart rate monitors were issued to workers in a hazardous and critical mining construction site. The ALIs that were recorded included heart rate and body temperature. Thresholds were established that alerted the monitoring safety staff when a worker exhibited potentially unsafe conditions. The results of the study demonstrated the feasibility of the system. Additionally, other results included worker resistance; non-disclosing of medical conditions, and limitations for IoT connectivity.

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Section: Iot For Construction Safetymentioning

confidence: 99%

Leading Indicators—A Conceptual IoT-Based Framework to Produce Active Leading Indicators for Construction Safety

Costin

Wehle

Adibfar

2019

Safety

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“…Additionally, by enabling devices to process and store data locally, less energy is required to maintain communication with external servers. Among all reviewed articles, 7 articles have not provided arguments related to the advantage of edge computing [49,56,81,102,105,110,118]. From Table 7, it can be seen that the reviewed articles have mentioned AD1 (61 articles), followed by AD4 (40 articles), AD5 (39 articles), AD2 (34 articles) and AD3 (21 articles) as advantages of edge computing.…”

Section: Rq3 -What Are the Advantages And Challenges Related To The D...mentioning

confidence: 99%

Combining Multiagent Systems with IoT forSmarter Buildings and Cities: a literature review

Luzolo

Galland

Elrawashdeh

et al. 2023

Preprint

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The Internet of Things (IoT) and Artificial Intelligence (AI) are two technologiesthat have long been applied to the development of smart systems. These systemscover various areas, such as smart cities, energy management, autonomous cars,etc. Intelligence, autonomy, and real-time monitoring are the fundamental ele-ments that characterize these application areas. The convergence of multi-agentsystems (MAS), IoT, and AI has opened up new possibilities for creating smarterbuildings and cities. This integration leverages the power of MAS to enable intelli-gent communication and collaboration among various entities, while IoT providesa vast network of interconnected sensors and devices that collect and transmitreal-time data. On the other hand, AI algorithms process and analyze this data toderive valuable insights and make informed decisions. Multi-agent systems tech-nology is one of the most used for the implementation of such intelligent systems.This article aims to focus on multi-agent systems, although it also covers otherrelated topics by carrying out a Systematic Literature Review (SLR) on relevantresearch works in the previous ten years. Eleven research questions are consideredat the beginning of the review, including typical research topics and applicationdomains. From the SLR results the research directions are: (i) Development ofa methodology that shows how to integrate the different applications indepen-dent of the scenarios that are deployed in. Additionally, elaboration of the toolsused in the integration process; (ii) Deployment of an agent in a microprocessor; (iii) How to implement and connect Multi-agent systems (MAS) technology andInternet of Things (IoT) devices (processors, controllers, sensors, and actuators).

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“…Haddad et al presented a framework for safety monitoring and management in the context of complex dynamic spatial environments, such as ports. (32) The framework combines IoT and multiagent geo-simulation techniques to build a realistic replication of the complex situation in a real port and to use this replication to assess worker safety from different userdefined safety perspectives. To reduce the environmental risk, PB components are not allowed to be hoisted in rain, snow, fog, or when the wind is stronger than level 6.…”

Section: Process Monitoring In On-site Assembly Phasementioning

confidence: 99%

Process Monitoring with Support of IoT in Prefabricated Building Construction

Yuan¹,

Ye²,

Lin³

2021

Sensors and Materials

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This paper focuses on how to use IoT technologies to monitor the project implementation process in prefabricated building (PB) construction, which will help optimize the construction schedule and ensure the quality and safety of PB construction. Although IoT monitoring can obtain a large amount of data during construction, the challenge is how to convert these data into intelligent information needed for feasible decision-making. Therefore, we need to clarify the key factors requiring monitoring during construction and how to use these data to make decisions. In this paper, we analyze the whole process of PB construction, comprising five phases: pre-construction, off-site manufacturing, delivery, on-site assembly, and finishing. Through mathematical model formulation to discover the key factors that affect the construction implementation process, we clarify the monitoring data that need to be obtained by IoT technologies. Using these monitoring data, it is possible to make judgments on process abnormalities, promptly give alarms, make proactive adjustments, and optimize the construction implementation process, thus achieving the goal of ensuring project quality and construction safety.

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A Multiagent Geosimulation and IoT-based Framework for Safety Monitoring in Complex Dynamic Spatial Environments

Cited by 10 publications

References 25 publications

Leading Indicators—A Conceptual IoT-Based Framework to Produce Active Leading Indicators for Construction Safety

Leading Indicators—A Conceptual IoT-Based Framework to Produce Active Leading Indicators for Construction Safety

Combining Multiagent Systems with IoT forSmarter Buildings and Cities: a literature review

Process Monitoring with Support of IoT in Prefabricated Building Construction

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