Advances in Smart Environment Monitoring Systems Using IoT and Sensors.

Silvia Liberata Ullo,G R Sinha

doi:10.3390/s20113113

Abstract

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.

Highlights

Introduction and BackgroundSustainable growth of the whole world depends on several factors such as economy, quality education, agriculture, industries and many others, but environment is one of the factors that plays the most important role
The backbone of the system is a wireless sensor networks (WSNs) that is establishing the actual interface between internet of things (IoT) devices and data captured through various types of smart sensors
There are a few components present in the air that help assessing the quality of the air; one such component, called PM2.5, was predicted in [78], using extreme machine learning techniques tested upon spatio-temporal data collected in a certain duration of time over a range of distances covered by the sensors

Summary

Introduction and Background

Sustainable growth of the whole world depends on several factors such as economy, quality education, agriculture, industries and many others, but environment is one of the factors that plays the most important role. The backbone of the system is a WSN that is establishing the actual interface between IoT devices and data captured through various types of smart sensors This is a perfect example of a “smart city” [11,25,26], using a SEM system that ensures healthy environment for its citizen. 3, where a SEM system is a smart agriculture monitoring system In this case, the health of soil, moisture analysis, water contamination level, water quantity level and several other factors are Sensors 2020, 20, 3113 very important in obtaining sustainable productivity in the agriculture sector. The part of the paper is organized as follows: We have briefly discussed the main issues related to environment monitoring, Section 2 discusses related research and study; Section 3 presents comparative analysis of advances in SEM, the role of IoT, AI and WSNs in implementing SEM.

Related Research and research

Findings and Challenges

Conclusions and Future