| Full text | |
| Author(s): |
Rangel, Rodrigo Kuntz
;
Maitelli, Andre Laurindo
;
Freitas, Joacy L., Jr.
;
de Araujo, Rhaclley F.
;
IEEE
Total Authors: 5
|
| Document type: | Journal article |
| Source: | 2023 IEEE AEROSPACE CONFERENCE; v. N/A, p. 19-pg., 2023-01-01. |
| Abstract | |
This paper describes the development of a wireless Drone charge station, navigation and control methodology using Artificial Intelligence and Computer Vision, based on Commercial-Of-The-Shelf (COTS) equipment and a dedicated management software to "help" a single Drone or a swarm squadron operation in VLOS and BVLOS, over urban regions. The Concept of Smart Cities consider the Drone use for power line asset monitoring, homeland security, delivery of medicine and logistics, epidemiological control and environmental monitoring. Due the modular design of the aerial platform and the wireless charge station, the use of COTS equipment allows more flexibility in all processes and result in cost reduction as well as development process optimization, where the focus is on the system integration. The wireless Drone charge station is a dedicated structure located at a strategic position within city limits, which is able to be used as communication relay, and to charge the Drones automatically via wireless, according the mission scope, increasing the Drone operation range over urban region. The sensors inside the wireless Drone charge station are IoT devices for the collection of meteorological data, images, command / control Drones and data from the other Stations, through a dedicated Command and Control Situation Room. By utilizing a dedicated management software at the Situation room - called by SIGI software - the system can control the drone and the airspace, collect field data from sensors and process them in real time. The situational analysis makes it possible to the administrator to optimize resources (material and human) by improving the efficiency of resource allocation in these areas while providing the real time situational awareness. The Drone design is a quadcopter with Embedded Artificial Intelligence and Computer Vision, defined as mission board, totally integrated with autopilot board and navigation sensors. A.I. and Computer vision are used to increase the Drone navigation precision, without a GPS-RTK/PPK device. In terms of mission requirements or customization, the Drone recognizes patterns and makes decisions according to each operational scope, e.g., visual identification of wireless charge stations, mosquito outbreaks, power lines assets in need of maintenance, swarm control for area saturation mapping and others. As described, this system focuses on a new concept of Smart Cities, the Drones as a Service Tool, to be employed in urban regions, helping the population in air mobility. (AU) | |
| FAPESP's process: | 18/10036-6 - Smart & Integrated Management System - smart cities |
| Grantee: | Rodrigo Kuntz Rangel |
| Support Opportunities: | Research Grants - Innovative Research in Small Business - PIPE |