Browsing by Author "Wijayasekara, S"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemEmbargo
    Genetic Algorithm-Based Unmanned Aerial Vehicle (UAV) Path Planning in Dynamic Environments for Disaster Management
    (Institute of Electrical and Electronics Engineers Inc., 2025) Wijerathne V.R; Theekshana W.G.P; Prabhanga K.G.B.; De Silva K.P.C; Wijayasekara, S; Weerathunga, I; Hansika, M. M.D.J.T
    Unmanned Aerial Vehicles (UAVs) hold immense potential in disaster management by enabling rapid response, real-time aerial reconnaissance, and improved situational awareness without endangering human lives. This research proposes a real-time UAV path-planning system based on a Hierarchical Recursive Multiagent Genetic Algorithm (HR-MAGA). Unlike traditional methods that struggle with adaptability in dynamic 3D environments, our system employs localized waypoint updates to reduce the computational cost of full-path recalculations. A multi-objective fitness function guides the optimization process by balancing safety, energy efficiency, altitude smoothness, turbulence resistance, and travel time. Additionally, the system integrates a decoupled real-time collision avoidance module for immediate response to sudden threats. While obstacle detection is abstracted in this study, the framework is designed to be easily integrated with real-time sensing technologies such as LiDAR for dynamic obstacle awareness. Experimental evaluations show a 20-30% improvement in path efficiency and a 40% increase in convergence speed compared to conventional genetic algorithms, highlighting the system's adaptability and robustness in disaster response scenarios.
  • Thumbnail Image
    ItemEmbargo
    LifeBeacon: Offline Emergency Communication and Victim Detection System for Disaster Areas
    (IEEE Computer Society, 2025) Senaratna S.M.T.S; Widanage W.T.N; Muhandiramge M.D.A.D.; Bandara H.K.K.T; Pandithage, D; Abeygunawardhana, P; Wijayasekara, S
    Natural disasters often compromise traditional communication infrastructure, significantly delaying emergency response and coordination efforts. This research presents a novel, disaster-resilient communication system designed to address these challenges through the integration of mobile ad-hoc networking and Wi-Fi-based victim localization. The proposed system comprises of a decentralized, infrastructure-less, self-healing mobile ad-hoc network (MANET) utilizing Bluetooth Low Energy (BLE) and Wi-Fi direct with an encrypted SOS messaging mechanism between end devices and a Wi-Fi probe request-based end device detection mechanism that estimates the location of affected individuals based on their mobile phones. If nodes disconnect, a self-healing algorithm guarantees automatic reconnection and uninterrupted message flow, while the ad-hoc network facilitates low-power, peer-to-peer communication without the need for traditional infrastructure. Both targeted and broadcast notifications are supported by the SOS messaging system, which is encrypted to protect the integrity and security of data. The victim localization system, meantime, makes precise estimates of the population and location of people in the disaster region using trilateration and Received Signal Strength Indicator (RSSI). Experimental evaluations conducted under simulated disaster conditions demonstrate the system's scalability, energy efficiency, and effectiveness in maintaining real-time communication and accurate victim tracking.