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| Title | Smart Drone Controller Framework—Toward An Internet Of Drones |
|---|---|
| ID_Doc | 50770 |
| Authors | Veerappan C.S.; Loh P.K.K.; Chennattu R.J. |
| Year | 2022 |
| Published | Studies in Computational Intelligence, 1002 |
| DOI | http://dx.doi.org/10.1007/978-981-16-7498-3_1 |
| Abstract | There has been an increasing trend to use multiple drones to cooperate autonomously beyond visual line-of-sight missions such as remote services, digital governance and planning, control of safety and security in a smart nation/smart city. In addition, machine learning (ML) has emerged as a key enabler to achieve efficiency in missions such as object detection and intruder detection. In this context, most of the commercially off-the-shelf Wi-Fi drones have limited resources and do not offer any firmware customization; these inherent limitations and technical gaps highlight the need for a software-based smart controller framework to realize support for a team of autonomous drones working together as an Internet of Drones (IoD). This can form the basis for strategic management of new Smart Cities that aim to optimize resources utilization and autonomize services. In this chapter, we present a preliminary architectural design to support needed capabilities and features of a cross-platform Smart Drone Controller (SDC) framework. An SDC framework supports a deployed team of Wi-Fi-based drones to conduct assigned missions collaboratively. The SDC’s ML engine has an option to choose algorithms according to the assigned mission. Overall, our SDC framework prototype improves the reliability of the team-based mission and enables a mixed selection of commercial drones to be deployed remotely and collaboratively as an IoD to create positive impact in service autonomy offered to smart city residents. This chapter details framework’s implementation and results with multiple Tello Edu drones assigned to an intruder drone detection mission. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. |
| Author Keywords | Computer vision; Controller framework; Drones; Machine learning; Object detection; Smart city; Surveillance; UAV |
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