Optimal Layered Resource Management and Data Processing for Threat Detection in Urban Environments
Optimal Layered Resource Management and Data Processing for Threat Detection in Urban Environments
批准号:
538404-2018
负责人:
Kirubarajan, ThiaT
金额:
$6.99万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
中文摘要
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英文摘要
Canada must be able to secure and protect the people and infrastructure in its urban environments. To do so, threats such as terrorist events and improvised explosive devices, in urban environments need to be identified early not only to safeguard the citizens and the infrastructure, but also to maintain the citizens' confidence in law and order and their trust in the government. In the case of threats that are mobile, it is also essential to accurately track and predict their kinematic states as they evolve over space and time. To detect such stationary or kinematic threats, sensors or signal sources such as cameras, radars, lidars, communication devices, radio and television stations, and cell phone towers can be used in an urban environment.In some urban scenarios, there might be an abundance of sensors due to ubiquitous cameras and cell phones, which could overload the communication and computational resources, or a dearth of accessible sensors due to the presence of buildings that block signal propagation, which would adversely affect the quality of threat detection and tracking. In either case, it is essential to strike a balance between (i) sensing, communication and computational resource utilization and (ii) the desired timeliness and accuracy of threat detection and tracking. This need to balance motivates the proposed research work to develop algorithms for optimal management of sensor, communication and computational resources as well as algorithms for threat detection and object tracking in urban environments using sensors and processors mounted on stationary or moving platforms. The proposed work will train a number of highly qualified personnel (HQP) in sensor and data processing with application to safety and security. In addition, the trained HQP can be employed and the resulting algorithms deployed in other fields such as autonomous vehicles, intelligent transportation and smart cities, which are of importance to maintain Canada's edge in today's high-tech world.
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