Collaborative sensing in internet of things: A comprehensive survey

S He, K Shi, C Liu, B Guo, J Chen… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Collaborative sensing leverages the cooperation of a collection of sensors to complete a
large-scale sensing task in Internet of Things (IoT). Although some previous studies have …

A survey of network lifetime maximization techniques in wireless sensor networks

H Yetgin, KTK Cheung, M El-Hajjar… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
Emerging technologies, such as the Internet of Things, smart applications, smart grids, and
machine-to-machine networks stimulate the deployment of autonomous, self-configuring …

[PDF][PDF] A PSO based energy efficient coverage control algorithm for wireless sensor networks.

J Wang, C Ju, Y Gao, AK Sangaiah… - Computers, Materials & …, 2018 - e-tarjome.com
Wireless Sensor Networks (WSNs) are large-scale and high-density networks that typically
have coverage area overlap. In addition, a random deployment of sensor nodes cannot fully …

The sensable city: A survey on the deployment and management for smart city monitoring

R Du, P Santi, M Xiao, AV Vasilakos… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
In last two decades, various monitoring systems have been designed and deployed in urban
environments, toward the realization of the so called smart cities. Such systems are based …

Cluster-based routing protocols in wireless sensor networks: A survey based on methodology

F Fanian, MK Rafsanjani - Journal of Network and Computer Applications, 2019 - Elsevier
In today's world that all sciences and technologies, including Wireless Sensor Networks
(WSNs) are dealing with the improvement of the existing solutions, we are looking for time …

Particle swarm optimization based clustering algorithm with mobile sink for WSNs

J Wang, Y Cao, B Li, H Kim, S Lee - Future Generation Computer Systems, 2017 - Elsevier
Wireless sensor networks with fixed sink node often suffer from hot spots problem since
sensor nodes close to the sink usually have more traffic burden to forward during …

Machine learning for advanced wireless sensor networks: A review

T Kim, LF Vecchietti, K Choi, S Lee… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Wireless sensor networks (WSNs) are typically used with dynamic conditions of task-related
environments for sensing (monitoring) and gathering of raw sensor data for subsequent …

Metasurface inverse design using machine learning approaches

X Shi, T Qiu, J Wang, X Zhao, S Qu - Journal of Physics D …, 2020 - iopscience.iop.org
Conventional metasurface design methods usually require a lot of computational resources
and time, meaning they fail to satisfy the efficient, rapid design on demand. On account of …

Machine learning for coverage optimization in wireless sensor networks: a comprehensive review

OS Egwuche, A Singh, AE Ezugwu, J Greeff… - Annals of Operations …, 2023 - Springer
In the context of wireless sensor networks (WSNs), the utilization of artificial intelligence (AI)-
based solutions and systems is on the ascent. These technologies offer significant potential …

Mate: Benchmarking multi-agent reinforcement learning in distributed target coverage control

X Pan, M Liu, F Zhong, Y Yang… - Advances in Neural …, 2022 - proceedings.neurips.cc
Abstract We introduce the Multi-Agent Tracking Environment (MATE), a novel multi-agent
environment simulates the target coverage control problems in the real world. MATE hosts …