Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimization
An Exigency Vehicle (EV) has to go more quickly to increase the likelihood that someone in danger would survive. Construction projects, strikes, and accidents may all be avoided with an effective vehicle routing solution. The Internet of Things (IoT) network simulation for Exigency Vehicle routing i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Franklin Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2773186323000518 |
| _version_ | 1797202933638496256 |
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| author | Sudipta Roy Dipak Kumar Jana Anjan Mishra |
| author_facet | Sudipta Roy Dipak Kumar Jana Anjan Mishra |
| author_sort | Sudipta Roy |
| collection | DOAJ |
| description | An Exigency Vehicle (EV) has to go more quickly to increase the likelihood that someone in danger would survive. Construction projects, strikes, and accidents may all be avoided with an effective vehicle routing solution. The Internet of Things (IoT) network simulation for Exigency Vehicle routing is proposed in this research utilizing a linguistic interval type 2 fuzzy logic system (LIT2FLS) based data fusion approach. The predicted effectiveness of our model for intelligent city applications, including emergency vehicle routing, is well demonstrated by the LIT2FLS correlation coefficients of 0.994%. This data fusion approach determines the exact level of congestion for a given place by combining sensory data with crowd reactions. In addition, OSRM employs a road communication system to detect real-time traffic variations and choose the least congested route. Furthermore, a sensor station for gathering the speeds and pollutants of moving automobiles on the road has also been established. An Android app has been developed to collect public information on blockages A driver of an Exigency Vehicle (EV) is directed towards a medical facility with the quickest, congestion-aware path by means of the Application software service. We have created an IT2FLS system that assists with decisions to calculate traffic congestion. Analyze the ability to scale and quickness of response associated with the suggested routing strategy. |
| first_indexed | 2024-03-09T01:32:00Z |
| format | Article |
| id | doaj.art-24b7f96aa1be4eca9d616bad5521489a |
| institution | Directory Open Access Journal |
| issn | 2773-1863 |
| language | English |
| last_indexed | 2024-04-24T08:11:19Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Franklin Open |
| spelling | doaj.art-24b7f96aa1be4eca9d616bad5521489a2024-04-17T04:50:28ZengElsevierFranklin Open2773-18632024-03-016100057Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimizationSudipta Roy0Dipak Kumar Jana1Anjan Mishra2Department of Computer Science Engineering(Cybar Security), Haldia Institute of Technology, Haldia, Purba Midnapur 721657, West Bengal, IndiaSchool of Applied Science & Humanities, Haldia Institute of Technology, Haldia Purba Midnapur 721657, West Bengal, India; Corresponding author.Haldia Institute of Technology, Haldia Purba Midnapur 721657, West Bengal, IndiaAn Exigency Vehicle (EV) has to go more quickly to increase the likelihood that someone in danger would survive. Construction projects, strikes, and accidents may all be avoided with an effective vehicle routing solution. The Internet of Things (IoT) network simulation for Exigency Vehicle routing is proposed in this research utilizing a linguistic interval type 2 fuzzy logic system (LIT2FLS) based data fusion approach. The predicted effectiveness of our model for intelligent city applications, including emergency vehicle routing, is well demonstrated by the LIT2FLS correlation coefficients of 0.994%. This data fusion approach determines the exact level of congestion for a given place by combining sensory data with crowd reactions. In addition, OSRM employs a road communication system to detect real-time traffic variations and choose the least congested route. Furthermore, a sensor station for gathering the speeds and pollutants of moving automobiles on the road has also been established. An Android app has been developed to collect public information on blockages A driver of an Exigency Vehicle (EV) is directed towards a medical facility with the quickest, congestion-aware path by means of the Application software service. We have created an IT2FLS system that assists with decisions to calculate traffic congestion. Analyze the ability to scale and quickness of response associated with the suggested routing strategy.http://www.sciencedirect.com/science/article/pii/S2773186323000518LIT2FLSIoTARMSenor nodeOSRMExigency Vehicle routing |
| spellingShingle | Sudipta Roy Dipak Kumar Jana Anjan Mishra Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimization Franklin Open LIT2FLS IoT ARM Senor node OSRM Exigency Vehicle routing |
| title | Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimization |
| title_full | Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimization |
| title_fullStr | Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimization |
| title_full_unstemmed | Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimization |
| title_short | Linguistic interval type 2 fuzzy logic-based Exigency Vehicle routing: IoT system development for smart city applications with soft computing-based optimization |
| title_sort | linguistic interval type 2 fuzzy logic based exigency vehicle routing iot system development for smart city applications with soft computing based optimization |
| topic | LIT2FLS IoT ARM Senor node OSRM Exigency Vehicle routing |
| url | http://www.sciencedirect.com/science/article/pii/S2773186323000518 |
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