RS-CPS: A distributed architecture of robotic surveillance cyber-physical system in the nature environment

Abstract

Modern nature surveillance systems are highly automated and require distributed architectures in order to increase understanding of the environment by integrating data from various monitors and sensors, which are mounted not only on fixed stations, but also on robotic actuators. In this paper, we propose a distributed architecture of robotic surveillance cyber-physical system (RS-CPS) in the nature environment, which is designed as integration of computation and physical processes. The RS-CPS system consists of five levels including smart connection, datato-information conversion, cyber communication, cognition, and configuration. Based on this architecture, the nature risk such as wildfires, the activities of wild animals and the climate changes in plants can be constantly monitored by the cooperation of multiple agents such as autonomous UAVs, robotic pan-tilt-zoom cameras, forest infrared cameras, songbird acoustic recorders, GPS tracking collars and ecological factor sensors located in field. The experiments demonstrate the feasibility and effectiveness of the new architecture.

Formation tracking of target moving on natural surfaces

“…These proposed solutions, among many others, are dedicated for urban environments where it is assumed the surface consists only of the base plane and quadrangular prisms lying on the base plane (i.e the target moves in planar path between buildings), and all UAVs fly at some altitude over the buildings which makes them free from natural obstacles. In addition, as the agents are so far from the target and the terrain, these facts make the targets always under the camera sight, i.e the relative speed between the target and the UAV's eyes is low, for which, in most cases the target can be even considered as static, the same points are noticed for [10] where the author did not even need to consider the occlusion and the collision avoidance, meanwhile our issue compels the UAVs to be very close to the target (5-20 m) to monitor a target moving on natural no-planar surface (mountainous surface), this fact increases mainly the probability of occlusion of the line of sight, and the collision with the mountainous surface, which push us to exclude these solutions adapted for the usual surveillance tasks where the agents hover out of the terrain folds, especially in urban environment.…”

“…Beside target tracking and formation control, this paper subject interests with other fields like surveillance and monitoring of moving objects. It is notable that most of surveillance studies [6]- [10], deal with urban environments, where the common objective is to monitor a static or moving target between urban buildings by means of single or multiple UAVs with on-board cameras. [8] proposed a novel occlusion-aware surveillance algorithm based on decomposition of the surveillance problem into a variant of the 3D art gallery problem and an instance of travelling salesman problem for Dubins vehicles, the algorithm yields a covering vantage points, each of which must be travelled by at least one UAV in a shortest path without need for coordination between agents.…”

A Cyber-Physical System for Wildfire Detection and Firefighting

“…Detecting and controlling wildfires is a challenging task, as they can spread rapidly and are difficult to anticipate. Researchers are exploring the use of advanced technologies such as IoT, robotics, and drone technologies [7]. The synergy of these technologies converges in a new trend that can be called the Internet of Robotics and Drone Things [8].…”

Cyber-Physical System Security Surveillance using Knowledge Graph based Digital Twins - A Smart Farming Usecase

“…Several fields, such as transportation, medical, military, etc., have developed surveillance applications. Surveillance for CPS is considered as an important application [7] in order to protect CPS from cyber-attacks and downtime. To achieve this in a smart farm ecosystem, we integrate our digital twin and CPS to detect abnormalities in sensors.…”