Advances in Smart Environment Monitoring Systems Using IoT and Sensors

Air quality, water pollution, and radiation pollution are major factors that pose genuine challenges in the environment. Suitable monitoring is necessary so that the world can achieve sustainable growth, by maintaining a healthy society. In recent years, the environment monitoring has turned into a...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2020-05, Vol.20 (11), p.3113
Main Authors: Ullo, Silvia Liberata, Sinha, G. R.
Format: Article
Language:English
Subjects:
Air monitoring
Air pollution
Air quality
Artificial intelligence
environment
Environmental monitoring
Health care
Internet of Things
internet of things (IoT)
Machine learning
Medical research
Monitoring systems
Noise reduction
pollution
Pollution monitoring
Review
Sensors
Smart cities
smart environment monitoring (SEM)
smart sensor
Water pollution
Water quality
Wireless networks
Wireless sensor networks
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Summary:Air quality, water pollution, and radiation pollution are major factors that pose genuine challenges in the environment. Suitable monitoring is necessary so that the world can achieve sustainable growth, by maintaining a healthy society. In recent years, the environment monitoring has turned into a smart environment monitoring (SEM) system, with the advances in the internet of things (IoT) and the development of modern sensors. Under this scenario, the present manuscript aims to accomplish a critical review of noteworthy contributions and research studies on SEM, that involve monitoring of air quality, water quality, radiation pollution, and agriculture systems. The review is divided on the basis of the purposes where SEM methods are applied, and then each purpose is further analyzed in terms of the sensors used, machine learning techniques involved, and classification methods used. The detailed analysis follows the extensive review which has suggested major recommendations and impacts of SEM research on the basis of discussion results and research trends analyzed. The authors have critically studied how the advances in sensor technology, IoT and machine learning methods make environment monitoring a truly smart monitoring system. Finally, the framework of robust methods of machine learning; denoising methods and development of suitable standards for wireless sensor networks (WSNs), has been suggested.
ISSN:1424-8220
1424-8220
DOI:10.3390/s20113113