{"title":"基于毫米波雷达的基于视觉、射频和物理传感器的无创车辆占用检测:综述","authors":"Jawad Yousaf;Alyssa Palmer;Maitha Shams;Zayna Wasma;Montasir Qasymeh;Taimur Hassan;Deepak Arora;Mohammed Ghazal","doi":"10.1109/JSEN.2025.3562685","DOIUrl":null,"url":null,"abstract":"The potential uses of human occupancy detection (HOD) in vehicles are crucial for handling resources, passenger safety, and privacy-preserving technology. In this study, the usage of various sensor systems for noninvasive vehicle occupant detection is examined, including millimeter-wave (mmWave) radar, vision-based, and physical sensors. These technologies undergo a thorough review analysis that looks at methods, performance indicators, and use cases before being assessed for robustness, accuracy, real-time capabilities, scalability, and cost-effectiveness. The impact of clutter, scalability, and privacy in car interiors on HOD is also thoroughly discussed. Based on its ability to balance cost, accuracy, and adaptability, frequency-modulated continuous-wave (FMCW) radar is termed the best option for vehicle occupant identification. The study discussed the possible challenges and future direction, as well as provided research opportunities in hybrid sensing systems and advanced machine learning integration to overcome existing constraints.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"18643-18661"},"PeriodicalIF":4.3000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"mmWave Radar-Based Noninvasive Vehicle Occupancy Detection With Insights From Vision, RF, and Physical Sensors: A Review\",\"authors\":\"Jawad Yousaf;Alyssa Palmer;Maitha Shams;Zayna Wasma;Montasir Qasymeh;Taimur Hassan;Deepak Arora;Mohammed Ghazal\",\"doi\":\"10.1109/JSEN.2025.3562685\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The potential uses of human occupancy detection (HOD) in vehicles are crucial for handling resources, passenger safety, and privacy-preserving technology. In this study, the usage of various sensor systems for noninvasive vehicle occupant detection is examined, including millimeter-wave (mmWave) radar, vision-based, and physical sensors. These technologies undergo a thorough review analysis that looks at methods, performance indicators, and use cases before being assessed for robustness, accuracy, real-time capabilities, scalability, and cost-effectiveness. The impact of clutter, scalability, and privacy in car interiors on HOD is also thoroughly discussed. Based on its ability to balance cost, accuracy, and adaptability, frequency-modulated continuous-wave (FMCW) radar is termed the best option for vehicle occupant identification. The study discussed the possible challenges and future direction, as well as provided research opportunities in hybrid sensing systems and advanced machine learning integration to overcome existing constraints.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":\"25 11\",\"pages\":\"18643-18661\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10977736/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10977736/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
mmWave Radar-Based Noninvasive Vehicle Occupancy Detection With Insights From Vision, RF, and Physical Sensors: A Review
The potential uses of human occupancy detection (HOD) in vehicles are crucial for handling resources, passenger safety, and privacy-preserving technology. In this study, the usage of various sensor systems for noninvasive vehicle occupant detection is examined, including millimeter-wave (mmWave) radar, vision-based, and physical sensors. These technologies undergo a thorough review analysis that looks at methods, performance indicators, and use cases before being assessed for robustness, accuracy, real-time capabilities, scalability, and cost-effectiveness. The impact of clutter, scalability, and privacy in car interiors on HOD is also thoroughly discussed. Based on its ability to balance cost, accuracy, and adaptability, frequency-modulated continuous-wave (FMCW) radar is termed the best option for vehicle occupant identification. The study discussed the possible challenges and future direction, as well as provided research opportunities in hybrid sensing systems and advanced machine learning integration to overcome existing constraints.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice