{"title":"使用物联网的智慧城市安全驱动的智能自动驾驶汽车","authors":"K. Balachander, C. Venkatesan, R. Kumar","doi":"10.1108/ijpcc-10-2020-0182","DOIUrl":null,"url":null,"abstract":"\nPurpose\nAutonomous vehicles rely on IoT-based technologies to take numerous decisions in real-time situations. However, added information from the sensor readings will burden the system and cause the sensors to produce inaccurate readings. To overcome these issues, this paper aims to focus on communication between sensors and autonomous vehicles for better decision-making in real-time. The system has unique features to detect the upcoming and ongoing vehicles automatically without intervention of humans in the system. It also predicts the type of vehicle and intimates the driver.\n\n\nDesign/methodology/approach\nThe system is designed using the ATmega 328 P and ESP 8266 chip. Information from ultrasonic and infrared sensors are analyzed and updated in the cloud server. The user can access all these real-time data at any point of time. The stored information in cloud servers is used for integrating artificial intelligence into the system.\n\n\nFindings\nThe real-time sensor information is used to predict the surrounding environment and the system responds to the user according to the situation.\n\n\nPractical implications\nThe system is implemented on embedded platform with IoT technology. The sensor information is updated to the cloud using the Blynk application for the user in real time.\n\n\nOriginality/value\nThe system is proposed for smart cities with IoT technology where the user and the system are aware of the surrounding environment. The system is mainly concerned with the accuracy of sensors and the distance between the vehicles in real-time environment.\n","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Safety driven intelligent autonomous vehicle for smart cities using IoT\",\"authors\":\"K. Balachander, C. Venkatesan, R. Kumar\",\"doi\":\"10.1108/ijpcc-10-2020-0182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nAutonomous vehicles rely on IoT-based technologies to take numerous decisions in real-time situations. However, added information from the sensor readings will burden the system and cause the sensors to produce inaccurate readings. To overcome these issues, this paper aims to focus on communication between sensors and autonomous vehicles for better decision-making in real-time. The system has unique features to detect the upcoming and ongoing vehicles automatically without intervention of humans in the system. It also predicts the type of vehicle and intimates the driver.\\n\\n\\nDesign/methodology/approach\\nThe system is designed using the ATmega 328 P and ESP 8266 chip. Information from ultrasonic and infrared sensors are analyzed and updated in the cloud server. The user can access all these real-time data at any point of time. The stored information in cloud servers is used for integrating artificial intelligence into the system.\\n\\n\\nFindings\\nThe real-time sensor information is used to predict the surrounding environment and the system responds to the user according to the situation.\\n\\n\\nPractical implications\\nThe system is implemented on embedded platform with IoT technology. The sensor information is updated to the cloud using the Blynk application for the user in real time.\\n\\n\\nOriginality/value\\nThe system is proposed for smart cities with IoT technology where the user and the system are aware of the surrounding environment. The system is mainly concerned with the accuracy of sensors and the distance between the vehicles in real-time environment.\\n\",\"PeriodicalId\":210948,\"journal\":{\"name\":\"Int. J. Pervasive Comput. Commun.\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Pervasive Comput. Commun.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/ijpcc-10-2020-0182\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Pervasive Comput. Commun.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijpcc-10-2020-0182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Safety driven intelligent autonomous vehicle for smart cities using IoT
Purpose
Autonomous vehicles rely on IoT-based technologies to take numerous decisions in real-time situations. However, added information from the sensor readings will burden the system and cause the sensors to produce inaccurate readings. To overcome these issues, this paper aims to focus on communication between sensors and autonomous vehicles for better decision-making in real-time. The system has unique features to detect the upcoming and ongoing vehicles automatically without intervention of humans in the system. It also predicts the type of vehicle and intimates the driver.
Design/methodology/approach
The system is designed using the ATmega 328 P and ESP 8266 chip. Information from ultrasonic and infrared sensors are analyzed and updated in the cloud server. The user can access all these real-time data at any point of time. The stored information in cloud servers is used for integrating artificial intelligence into the system.
Findings
The real-time sensor information is used to predict the surrounding environment and the system responds to the user according to the situation.
Practical implications
The system is implemented on embedded platform with IoT technology. The sensor information is updated to the cloud using the Blynk application for the user in real time.
Originality/value
The system is proposed for smart cities with IoT technology where the user and the system are aware of the surrounding environment. The system is mainly concerned with the accuracy of sensors and the distance between the vehicles in real-time environment.