Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Application of Low-Cost IoT Sensors for Smart Public Transportation
https://orcid.org/http://orcid.org/0000-0002-1137-9656
Smart public transportation is one of the main components of a smart city. The current work develops a low-cost Internet of Things (IoT) solution to estimate occupancy and monitor fine particulate matter (PM2.5) levels in public transit to aid smart public transportation applications. For the same, an IoT module equipped with a Wi-Fi Media Access Control (MAC) scanner, Global Positioning System (GPS) module, and PM2.5 sensor is developed and evaluated in public transport buses in Chennai, India. A two-level filtration algorithm is proposed for Wi-Fi-GPS-fused data to estimate real-time occupancies. The results indicate that the developed module is a feasible solution to provide real-time occupancy estimates on a bus at a lower cost. In addition to cost, another advantage of the proposed occupancy estimation method is that it can be used for other applications, such as origin-destination estimation. The PM2.5 inside the bus was also estimated, and the correlation between the PM2.5 levels in the cabin and the occupancy of the passengers on board was calculated. In the analyzed trips, a significant positive correlation between occupancy and PM2.5 was observed, suggesting that as occupancy increases, air quality can be compromised by increased human resuspension activities. Recognizing this relationship is crucial for policymakers and transport authorities, as it highlights the need for efficient ventilation systems and regular air quality inspections in public transportation, particularly during peak hours, to protect the health and comfort of passengers. The novelty of the developed IoT module lies in providing a low-cost and easily deployable IoT solution for smart public transportation.
Application of Low-Cost IoT Sensors for Smart Public Transportation
https://orcid.org/http://orcid.org/0000-0002-1137-9656
Smart public transportation is one of the main components of a smart city. The current work develops a low-cost Internet of Things (IoT) solution to estimate occupancy and monitor fine particulate matter (PM2.5) levels in public transit to aid smart public transportation applications. For the same, an IoT module equipped with a Wi-Fi Media Access Control (MAC) scanner, Global Positioning System (GPS) module, and PM2.5 sensor is developed and evaluated in public transport buses in Chennai, India. A two-level filtration algorithm is proposed for Wi-Fi-GPS-fused data to estimate real-time occupancies. The results indicate that the developed module is a feasible solution to provide real-time occupancy estimates on a bus at a lower cost. In addition to cost, another advantage of the proposed occupancy estimation method is that it can be used for other applications, such as origin-destination estimation. The PM2.5 inside the bus was also estimated, and the correlation between the PM2.5 levels in the cabin and the occupancy of the passengers on board was calculated. In the analyzed trips, a significant positive correlation between occupancy and PM2.5 was observed, suggesting that as occupancy increases, air quality can be compromised by increased human resuspension activities. Recognizing this relationship is crucial for policymakers and transport authorities, as it highlights the need for efficient ventilation systems and regular air quality inspections in public transportation, particularly during peak hours, to protect the health and comfort of passengers. The novelty of the developed IoT module lies in providing a low-cost and easily deployable IoT solution for smart public transportation.
Application of Low-Cost IoT Sensors for Smart Public Transportation
https://orcid.org/http://orcid.org/0000-0002-1137-9656
Smart public transportation is one of the main components of a smart city. The current work develops a low-cost Internet of Things (IoT) solution to estimate occupancy and monitor fine particulate matter (PM2.5) levels in public transit to aid smart public transportation applications. For the same, an IoT module equipped with a Wi-Fi Media Access Control (MAC) scanner, Global Positioning System (GPS) module, and PM2.5 sensor is developed and evaluated in public transport buses in Chennai, India. A two-level filtration algorithm is proposed for Wi-Fi-GPS-fused data to estimate real-time occupancies. The results indicate that the developed module is a feasible solution to provide real-time occupancy estimates on a bus at a lower cost. In addition to cost, another advantage of the proposed occupancy estimation method is that it can be used for other applications, such as origin-destination estimation. The PM2.5 inside the bus was also estimated, and the correlation between the PM2.5 levels in the cabin and the occupancy of the passengers on board was calculated. In the analyzed trips, a significant positive correlation between occupancy and PM2.5 was observed, suggesting that as occupancy increases, air quality can be compromised by increased human resuspension activities. Recognizing this relationship is crucial for policymakers and transport authorities, as it highlights the need for efficient ventilation systems and regular air quality inspections in public transportation, particularly during peak hours, to protect the health and comfort of passengers. The novelty of the developed IoT module lies in providing a low-cost and easily deployable IoT solution for smart public transportation.
Application of Low-Cost IoT Sensors for Smart Public Transportation
Transp. in Dev. Econ.
Patra, Satya S. (Autor:in) / Vanajakshi, Lelitha (Autor:in)
01.10.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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