System-Level Performance Analysis of Cooperative Multiple Unmanned Aerial Vehicles for Wildfire Surveillance Using Agent-Based Modeling

Abstract

In this paper, we propose an agent-based approach for the evaluation of Multiple Unmanned Autonomous Vehicle (MUAV) wildfire monitoring systems for remote and hard-to-reach areas. Emerging environmental factors are causing a higher number of wildfires and keeping these fires in check is becoming a global challenge. MUAV deployment for the monitoring and surveillance of potential fires has already been established. However, most of the scholarly work is still focused on MUAV operations details. In wildfire surveillance and monitoring, evaluations of the system-level performance in terms of the analysis of the effects of individual behavior on system surveillance has yet to be established. Especially in an MUAV system, the individual and cooperative behaviors of the team affect the overall performance of the system. Such systems are dynamic and stochastic because of an ever-changing environment. Quantifying the emergent system behavior and general performance measures of such a system by analytical methods is challenging. In our work, we present an agent-based model for MUAV surveillance missions. This paper focuses on the overall system performance of cooperative UAVs performing forest fire surveillance. The principal theme is to present the effects of three behaviors on overall performance: (1) the area allocation and (2) dynamic coverage, and (3) the effects of forest density on team allocation. For area allocation, three behaviors are simulated: (1) randomized, (2) two-layer barrier sweep coverage, and (3) full sweep coverage. For dynamic coverage, the effects of communication and resource unavailability during the mission are studied by analyzing the agent’s downtime spent on refueling. Last, an extensive simulation is carried out on wildfire models with varying forest density. It is found that cooperative complete sweep coverage strategies perform better than the rest and the performance of the team is greatly affected by the forest density.

Accuracy Assessment of Drone Real-Time Open Burning Imagery Detection for Early Wildfire Surveillance

“…To highlight the main existing works, the sensor nodes can be communicated by using Long-Range (LoRa) devices as the wireless link to locate the fire sources. Meanwhile, UAV trends indicate that multiple UAVs (MUAVs) can be applied to forest density by using the agent-based method [29], which is a platform for early wildfire surveillance. The camera networks for early wildfire surveillance can be split into aerial cameras and watchtower cameras for terrestrial imagery.…”

A Control-Theoretic Spatio-Temporal Model for Wildfire Smoke Propagation Using UAV-Based Air Pollutant Measurements

“…Compared to the early wildfire detection methods described above, the proposed solution is more economical. Low-cost UAVs have been utilized in a broad range of applications [7,8], including remote chemical sensing [9,10] and modeling [11]. In our previous work, we developed a UAV and air quality sensor package for monitoring wildfire air toxins [12].…”

Using Explainable Artificial Intelligence (XAI) to Predict the Influence of Weather on the Thermal Soaring Capabilities of Sailplanes for Smart City Applications

“…They can aid in disaster management by surveying difficult-to-reach locations post-event [13]. They can help firefighters to correctly manage wildfires [14]. They are especially pertinent in flood detection and monitoring [15], as UAVs are more capable of providing the necessary aerial images than their satellite counterparts [16].…”

“…However, during competitions, pilots can reach average speeds exceeding 135 km/h over 750 km lengths, with the highest performing gliders (https://www.fai.org/news/looking-forward-2023-gliding-competition-season, accessed on 11 October 2023). Also, many proposed application areas are not as timesensitive but require extensive flight times such as constant wildfire monitoring [14], environmental monitoring [26] and general surveillance [23]. Therefore, the issue of flight interruptions to enable soaring would not be a dramatic issue and could be solved by using a fleet of UAVs.…”