TY - JOUR
T1 - WSN Architectures for Environmental Monitoring Applications
AU - Adu-Manu, Kofi Sarpong
AU - Abdulai, Jamal Deen
AU - Engmann, Felicia
AU - Akazue, Moses
AU - Appati, Justice Kwame
AU - Baiden, Godwill Enchill
AU - Sarfo-Kantanka, Godwin
N1 - Publisher Copyright:
© 2022 Kofi Sarpong Adu-Manu et al.
PY - 2022
Y1 - 2022
N2 - Wireless sensor networks (WSNs) have become ubiquitous, permeating every aspect of human life. In environmental monitoring applications (EMAs), WSNs are essential and provide a holistic view of the deployed environment. Physical sensor devices and actuators are connected across a network in environmental monitoring applications to sense vital environmental factors. EMAs bring together the intelligence and autonomy of autonomous systems to make intelligent decisions and communicate them using communication technologies. This paper discusses the various architectures developed for WSNs in environmental monitoring applications and the support for specific design goals, including machine learning in WSNs and its potential in environmental monitoring applications.
AB - Wireless sensor networks (WSNs) have become ubiquitous, permeating every aspect of human life. In environmental monitoring applications (EMAs), WSNs are essential and provide a holistic view of the deployed environment. Physical sensor devices and actuators are connected across a network in environmental monitoring applications to sense vital environmental factors. EMAs bring together the intelligence and autonomy of autonomous systems to make intelligent decisions and communicate them using communication technologies. This paper discusses the various architectures developed for WSNs in environmental monitoring applications and the support for specific design goals, including machine learning in WSNs and its potential in environmental monitoring applications.
UR - http://www.scopus.com/inward/record.url?scp=85138333277&partnerID=8YFLogxK
U2 - 10.1155/2022/7823481
DO - 10.1155/2022/7823481
M3 - Review article
AN - SCOPUS:85138333277
SN - 1687-725X
VL - 2022
JO - Journal of Sensors
JF - Journal of Sensors
M1 - 7823481
ER -