{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T07:29:57Z","timestamp":1769066997015,"version":"3.49.0"},"reference-count":20,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2021,12,7]],"date-time":"2021-12-07T00:00:00Z","timestamp":1638835200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJPCC"],"published-print":{"date-parts":[[2021,12,10]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The system is designed using the ATmega 328\u2009P 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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The real-time sensor information is used to predict the surrounding environment and the system responds to the user according to the situation.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ijpcc-10-2020-0182","type":"journal-article","created":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T07:50:56Z","timestamp":1638517856000},"page":"563-582","source":"Crossref","is-referenced-by-count":36,"title":["Safety driven intelligent autonomous vehicle for smart cities using IoT"],"prefix":"10.1108","volume":"17","author":[{"given":"K.","family":"Balachander","sequence":"first","affiliation":[]},{"given":"C.","family":"Venkatesan","sequence":"additional","affiliation":[]},{"given":"Kumar","family":"R.","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2021,12,7]]},"reference":[{"key":"key2021123111191812000_ref001","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/SMARTSENS.2015.7873595","article-title":"Quality of obstacle distance measurement using ultrasonic sensor and precision of two computer vision-based obstacle detection approaches","year":"2015"},{"key":"key2021123111191812000_ref002","first-page":"191","article-title":"Autonomous cars: past, present and future a review of the developments in the last century, the present scenario and the expected future of autonomous vehicle technology","year":"2015"},{"key":"key2021123111191812000_ref003","first-page":"1652","article-title":"Driver-activity recognition in the context of conditionally autonomous driving","year":"2015"},{"issue":"1928","key":"key2021123111191812000_ref004","first-page":"4649","article-title":"Autonomous driving in urban environments: approaches, lessons and challenges","volume":"368","year":"2010","journal-title":"Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences"},{"issue":"2","key":"key2021123111191812000_ref005","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1109\/JSEN.2001.936931","article-title":"An ultrasonic sensor for distance measurement in automotive applications","volume":"1","year":"2001","journal-title":"IEEE Sensors Journal"},{"issue":"2","key":"key2021123111191812000_ref006","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1109\/19.492808","article-title":"Ultrasonic distance sensor improvement using a two-level neural network","volume":"45","year":"1996","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"key2021123111191812000_ref007","first-page":"235","article-title":"Security threats to automotive can networks-practical examples and selected short-term countermeasures","year":"2008"},{"key":"key2021123111191812000_ref008","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/978-3-540-87698- 4_21","article-title":"Security threats to automotive CAN networks \u2013 practical examples and selected short-term counter measures","year":"2021"},{"issue":"2","key":"key2021123111191812000_ref009","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.1109\/COMST.2018.2869360","article-title":"Autonomous cars: research results, issues, and future challenges","volume":"21","year":"2019","journal-title":"IEEE Communications Surveys and Tutorials"},{"key":"key2021123111191812000_ref010","first-page":"1","article-title":"Internet of vehicles and autonomous connected car - 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