Things in the Air: Tagging Wearable IoT Informationon Drone Videos

Abstract

Drones have been applied to a wide range of security and surveillance applications recently. With drones, Internet of Things are extending to3D space. An interesting question is: Can we conduct person identification(PID) in a drone view? Traditional PID technologies such as RFID and fingerprint/iris/face recognition have their limitations or require close contactto specific devices. Hence, these traditional technologies can not be easily deployed to drones due to dynamic change of view angle and height. In this work,we demonstrate how to retrieve IoT data from users’ and correctly tag themon the human objects captured by a drone camera to identify and track groundhuman objects. First, we retrieve human objects from videos and conduct coordination transformation to handle the change of drone positions. Second,a fusion algorithm is applied to measure the correlation of video data andinertial data based on the extracted human motion features. Finally, we cancouple human objects with their wearable IoT devices, achieving our goal oftagging wearable device data such as personal profiles) on human objects ina drone view. Our experimental evaluation shows a recognition rate of 98.9%.To the best of our knowledge, this is the first work integrating videos fromdrone cameras and IoT data from inertial sensors.

Research and application of node fuzzy identification and localization in wireless sensor networks

“…Through the cooperative work between nodes, it realizes the detection, collection and processing of target information in the network coverage area, and transmits the information to the monitoring terminal through wireless multi-hop mode. [1][2][3][4] WSN have the characteristics of self-organization, rapid deployment and strong concealment. At the same time, sensor nodes have the characteristics of small size and low cost.…”

Discover Internet of Things editorial, inaugural issue

“… “Things in the Air: Tagging Wearable IoT Information on Drone Videos,” authored by Lan-Da Van, Ling-Yan Zhang, Chun-Hao Chang, Kit-Lun Tong, Kun-Ru Wu, and Yu-Chee Tseng, describes a surveillance system which employs drones that interact with wearable IoT devices for person identification. We expect to add one or two more papers in the inaugural issue [ 5 ]. …”