Smart Environment Monitoring System Research Articles

Integration of Wireless Sensor Network and IoT for Smart Environment Monitoring System

Air contamination, water waste, and radioactive contamination are significant environmental issues. Adequate supervision is needed to ensure economic sustainability through the preservation of a good society. Environmental tracking has become a Smart environment monitoring (SEM) system in recent times, with developments in the Internet of Things and the creation of advanced detectors. This situation evaluates substantial achievements and scientific studies on SEM, including air quality control, water management, radiation emissions, and agricultural practices. A Wireless sensor network and IoT integrated system for Smart environment monitoring (WSN-IoT-SEC) framework are proposed in this research. The analysis will be divided employing SEM techniques applications, and each aim will then be further studied in terms of the detectors, machine learning models, and classifiers operated. A systematic study was carried out based on the study’s evaluated results and patterns, indicating important suggestions and the SEM analysis’s influence. The researchers have discussed objectively how the advancements in mobile technologies, IoT, and wireless sensor networks allow the control of the atmosphere an intelligent monitoring device. Eventually, the concept of rigorous machine learning techniques has been proposed, denouncing techniques and developing appropriate WSN specifications.

Balikpapan’s wind analysis to determine air quality monitoring point to support smart environment monitoring system

In this industrial era, air pollution become a concerning problem since it can cause some respiratory problems. One of the air pollutions was Sulphur dioxide which dilutes fast in atmospheric water vapor resulting in acid rain which can affect the organism. Thus, in this research, we study the probability of the receptor’s location according to wind direction, as the preliminary information on deciding monitoring point. The meteorological data were obtained from Balikpapan’s Agency for Meteorological, Climatological, and Geophysics. The wind data was then plotted using a wind rose plot program called WRPLOT. Afterward, the dominant wind speed and direction will then be analyzed using google earth to know which point will be affected by the pollution dispersion from the chimney in Balikpapan. The results show that wind in Balikpapan throughout 2020 mostly blew from Southwest to Northeast Direction. Thus, the most probable receptor locations were open green spaces with no settlement around. This will have less impact on human health. Nevertheless, further research can be conducted to know better the on-air dispersion model around the power plant, how the green plant will be suffered from this air pollution, and how this pollution will affect the workers around it.

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 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.

IoT-Based Smart Environment Monitoring System for Air Pollutant Detection in Kuantan, Pahang, Malaysia

Air pollution is one of the pollutions that release harmful chemicals and if not controlled, it will affect the human respiratory system. Currently, there are two Air Pollution Monitoring system located in Kuantan district to record the pollution’s reading once it detects the air pollutant however, the origin of the pollution cannot be detected by the system. As a solution, a Smart Environment Monitoring System for Air Pollution Using Internet of Things (IoTs) is developed to overcome the weaknesses. This project involved both hardware and software developments, in which hardware development includes the Arduino Uno, Carbon Monoxide (MQ 7), smoke/gas (MQ 135) sensors, a buzzer and LCD display. This system is design so that the current reading can be viewed by admin in a real-time value. Besides, they can also view the data for every 8 hours. These data can be printed in PDF format. In addition, when the reading reached unhealthy value, it will warn the community via its alarm system embedded in this system. However, this system is subject to limitation especially on data delays from sensors to database. As only one existing monitoring system that located at Beserah, thus this new feature will add a sub-sensor that located at the designated area which potentially expose to the air pollution.

An Intelligent and Smart Environment Monitoring System for Healthcare

Skin wound healing is influenced by two kinds of environment i.e., exterior environment that is nearby to wound surface and interior environment that is the environment of the adjacent part under wound surface. Both types of environment play a vital role in wound healing, which may contribute to continuous or impaired wound healing. Although, different previous studies provided wound care solutions, but they focused on single environmental factors either wound moisture level, pH value or healing enzymes. Practically, it is insignificant to consider environmental effect by determination of single factors or two, as both types of environment contain a lot of other factors which must be part of investigation e.g., smoke, air pollution, air humidity, temperature, hydrogen gases etc. Also, previous studies didn’t classify overall healing either as continuous or impaired based on exterior environment effect. In current research work, we proposed an effective wound care solution based on exterior environment monitoring system integrated with Neural Network Model to consider exterior environment effect on wound healing process, either as continuous or impaired. Current research facilitates patients by providing them intelligent wound care solution to monitor and control wound healing at their home.

Data Storage in the Fog Computing for Smart Environment Monitoring System (SEMS)

Environment monitoring system for smart cities uses diverse kind of sensors which is used to accumulate the information for managing the resources efficiently. Environment monitoring system provides services such as automation of home, weather monitoring, air quality management and prediction of pollution. This paper presents the customized design on environment monitoring the basic parameters are temperature, humidity and CO2. These sensed data need to be stored and processed. In previous system, sensed data are stored using cloud computing. In proposed system, Fog computing is used to store the sensed data from smart environment monitoring system (SEMS) and transfer the data to the mobile app from the fog device which is more efficient than cloud computing.

Smart Environment Monitoring System by Employing Wireless Sensor Networks on Vehicles for Pollution Free Smart Cities

With the progression of advancements in technology, several innovations has been made in the field of communications that are transiting to Internet of Things. In this domain, Wireless Sensor Networks (WSN) are one of those independent sensing devices to monitor physical and environmental conditions along with thousands of applications in other fields. As air pollution being a major environmental change that causes many hazardous effects on human beings that need to be controlled. Hence, we deployed WSN nodes for constant monitoring of the air pollution around the city and the moving public transport buses and cars. This methodology gave us the monitoring data from the stationary nodes deployed in the city to the mobile nodes on Public Transport buses and cars. The data of the air pollution particles such as gases, smoke and other pollutants is collected via sensors on the Public transport buses and the data is being analyzed when the buses and cars reach back to the source destination after passing through the stationary nodes around the city. Our proposed architecture having innovative mesh network will be more efficient way of gathering data from the nodes of WSN. It will have lots of benefits with respect to the future concept of Smart Cities that will have the new technologies related to Internet of Things.