Exploring the Transition from Classical Approaches to Machine Learning Techniques for Coverage Estimation in Wireless Sensor Networks

., Mini (2024) Exploring the Transition from Classical Approaches to Machine Learning Techniques for Coverage Estimation in Wireless Sensor Networks. B P International, pp. 83-95. ISBN 978-81-970279-6-3

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Abstract

In the modern era, wireless sensor networks have become crucial due to their ability to operate within size constraints. Networks can be influenced by various internal and external factors, leading to effective changes. Conventional methods were designed for stable networks, which may not be suitable for dynamic networks. Here, machine learning techniques can be utilized for dynamic networks. In this chapter, we explore machine learning techniques that are well-suited for estimating coverage in wireless sensor networks.

Item Type: Book
Subjects: Eprints STM archive > Multidisciplinary
Depositing User: Unnamed user with email admin@eprints.stmarchive
Date Deposited: 12 Feb 2024 10:12
Last Modified: 12 Feb 2024 10:12
URI: http://public.paper4promo.com/id/eprint/1843

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