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Title	Comprehensive Analysis Of Data Collection Approaches In Wireless Sensor Networks
ID_Doc	15297
Authors	Mahmoud A.A.; Al-Mahdi H.; Ali A.F.; Abd El Salam K.; Elgohary R.
Year	2024
Published	Lecture Notes on Data Engineering and Communications Technologies, 220
DOI	http://dx.doi.org/10.1007/978-3-031-71619-5_20
Abstract	Wireless Sensor Networks (WSNs) play a pivotal role in diverse real-time applications such as Internet of Things, agriculture, smart cities, transportation, and surveillance, necessitating efficient and optimal data collection strategies. This study contributes to the advancement of knowledge by presenting a contemporary and exhaustive analysis of prevalent research trends in data collection methods within WSNs. We inaugurate our investigation with a meticulous taxonomy encompassing an extensive spectrum of techniques deployed for data collection in WSNs. Subsequently, we conduct a thorough and expansive survey of the pertinent literature, thereby furnishing a comprehensive panorama of the existing landscape of data collection in WSNs. In addition to the aforementioned, our inquiry critically engages with an in-depth analysis and discourse on diverse data collection schemes. By meticulously scrutinizing the resemblances and disparities among these schemes, we unveil their distinctive attributes and nuanced trade-offs. Furthermore, we discern and deliberate upon the myriad challenges intrinsic to data collection in WSNs, elucidating their implications. Lastly, we proffer a forward-looking perspective by delineating prospective avenues for research in the realm of data collection in WSNs. This encompasses latent domains for enhancement, nascent technologies, and pioneering methodologies poised to surmount extant challenges and amplify the efficacy and potential of data collection within WSNs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Author Keywords	Clustering; Data Collection; Internet of Things; Mobile Sink; Unmanned Aerial Vehicle; Wireless Sensor Networks

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