UAV-Driven Sustainable and Quality-Aware Data Collection in Robotic Wireless Sensor Networks

Currently, analysts in a variety of nations have developed various WSN clustering protocols. The major characteristic is the Low Energy Adaptive Clustering Hierarchy (LEACH), which attained the objective of energy balance by sporadically varying the Cluster Heads (CHs) in the region. Nevertheless, because it implements an arbitrary number system, the appropriateness of CH is complete with suspicions. In this paper, an optimal cluster head selection (CHS) model is developed regarding secure and energy-aware routing in the Wireless Sensor Network (WSN). Here, optimal CH is preferred based on distance, energy, security (risk probability), delay, trust evaluation (direct and indirect trust), and Received Signal Strength Indicator (RSSI). Here, the energy level is predicted using an improved Deep Convolutional Neural Network (DCNN). To choose the finest CH in WSN, Bald Eagle Assisted SSA (BEA-SSA) is employed in this work. Finally, the results authenticate the effectiveness of BEA-SSA linked to trust, RSSI, security, etc. The Packet Delivery Ratio (PDR) for 100 nodes is 0.98 at 500 rounds, which is high when compared to Grey Wolf Optimization (GWO), Multi-Objective Fractional Particle Lion Algorithm (MOFPL), Sparrow Search Algorithm (SSA), Bald Eagle Search optimization (BES), Rider Optimization (ROA), Hunger Games Search (HGS), Shark Smell Optimization (SSO), Rider-Cat Swarm Optimization (RCSO), and Firefly Cyclic Randomization (FCR) methods.

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Optimal Cluster Head Selection in WSN with Convolutional Neural Network-Based Energy Level Prediction

Gurumoorthy¹,

Subhash

Prado

et al. 2022

“…The proposed approach will apply to various application environments and sink node types. In the point of dynamic WSN, some related studies have begun to focus on mobile sink nodes in recent years [ 6 , 7 ] and find optimal roving paths for robot sink nodes [ 8 ]. It solves the limited energy problem of traditional sensors.…”

Section: Introductionmentioning

confidence: 99%

A Near-Optimal Energy Management Mechanism Considering QoS and Fairness Requirements in Tree Structure Wireless Sensor Networks

Tai

Liu

Hsiao

et al. 2023

The rapid development of AIOT-related technologies has revolutionized various industries. The advantage of such real-time sensing, low costs, small sizes, and easy deployment makes extensive use of wireless sensor networks in various fields. However, due to the wireless transmission of data, and limited built-in power supply, controlling energy consumption and making the application of the sensor network more efficient is still an urgent problem to be solved in practice. In this study, we construct this problem as a tree structure wireless sensor network mathematical model, which mainly considers the QoS and fairness requirements. This study determines the probability of sensor activity, transmission distance, and transmission of the packet size, and thereby minimizes energy consumption. The Lagrangian Relaxation method is used to find the optimal solution with the lowest energy consumption while maintaining the network’s transmission efficiency. The experimental results confirm that the decision-making speed and energy consumption can be effectively improved.

“…In recent years, Unmanned Aerial Vehicles (UAVs) have been developing toward miniaturization and intelligence, as a kind of aerial robot. In particular, due to their Vertical Take-Off and Landing (VTOL) and hovering capabilities, multi-rotor UAVs have been used in many military or civil fields, such as photography [ 1 ], mapping [ 2 ], agriculture [ 3 , 4 ], inspection [ 5 ], monitoring [ 6 , 7 ], and data collection [ 8 , 9 ]. However, these applications are utilized for observation and perception, which have no direct contact with the surrounding environment.…”

Section: Introductionmentioning

confidence: 99%

Robust Control Based on Adaptive Neural Network for the Process of Steady Formation of Continuous Contact Force in Unmanned Aerial Manipulator

Fang

Mao

Shen

et al. 2023

Contact force control for Unmanned Aerial Manipulators (UAMs) is a challenging issue today. This paper designs a new method to stabilize the UAM system during the formation of contact force with the target. Firstly, the dynamic model of the contact process between the UAM and the target is derived. Then, a non-singular global fast terminal sliding mode controller (NGFTSMC) is proposed to guarantee that the contact process is completed within a finite time. Moreover, to compensate for system uncertainties and external disturbances, the equivalent part of the controller is estimated by an adaptive radial basis function neural network (RBFNN). Finally, the Lyapunov theory is applied to validate the global stability of the closed-loop system and derive the adaptive law for the neural network weight matrix online updating. Simulation and experimental results demonstrate that the proposed method can stably form a continuous contact force and reduce the chattering with good robustness.