Low-Cost Energy-Efficient Air Quality Monitoring System Using Wireless Sensor Network

Khedo, Kavi Kumar; Chikhooreeah, Vishwakarma

doi:10.5772/intechopen.70138

Cited by 12 publications

(6 citation statements)

References 13 publications

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“…Referensi [7] membahas mengenai penggunaan sensor MQ-7 sebagai detektor asap rokok dengan fitur notifikasi melalui SMS. Referensi [8] membahas tentang sistem pemantauan kualitas udara yang menggunakan ThingSpeak IoT. Referensi [9] membahas tentang sistem keamanan rumah yang diimplementasikan dengan sensor PIR sebagai pendeteksi gerakan dan Wemos board mikrokontroler dilengkapi sistem notifikasi melalui platform IoT Blynk dan sistem monitoring dengan Thingspeak.…”

Section: Pendahuluanunclassified

Sistem Monitoring dan Notifikasi Kualitas Udara dalam Ruangan dengan Platform IoT

Waworundeng

Lengkong

2018

CogITo Smart Journal

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Penelitian ini membahas tentang prototipe alat pendeteksi kualitas udara di dalam ruangan dengan menggunakan mikrokontoler Wemos dan sensor MQ135 yang terhubung dengan platform IoT sebagai sistem monitoring dan notifikasi. Modul sensor MQ135 sebagai detektor kualitas udara, mengirimkan sinyal input untuk diproses oleh mikrokontroler Wemos board. Modul wifi yang terdapat pada Wemos board mengirimkan nilai yang terbaca oleh sensor ke platform IoT Thingspeak yang merekam data logging dalam bentuk grafik. Dalam hal ini, Thingspeak berfungsi sebagai bagian dari sistem monitoring. Sedangkan sebagai sistem notifikasi digunakan platform IoT Blynk apps. Blynk apps terhubung secara tidak langsung ke prototipe alat pendeteksi kualitas udara melalui internet. Nilai yang terbaca dari sensor diproses sesuai program dan jika memenuhi level sensor yang ditentukan maka sistem memberikan notifikasi kepada user melalui Blynk apps. Sistem ini berpotensi untuk digunakan sebagai sistem pemantauan kualitas udara di dalam ruangan untuk meningkatkan kesadaran tentang pentingnya kualitas udara yang sehat.Keywords : Sistem Monitoring, Notifikasi, Kualitas Udara, Sensor, Iot

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Section: Pendahuluanunclassified

Sistem Monitoring dan Notifikasi Kualitas Udara dalam Ruangan dengan Platform IoT

Waworundeng

Lengkong

2018

CogITo Smart Journal

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“…In [14] build cost efficient energy model for air pollution monitoring system with wireless network. They used hierarchical based genetic algorithm for this monitoring.…”

Section: Literature Reviewmentioning

confidence: 99%

Air Pollution Prediction Using Dual Graph Convolution LSTM Technique

Ram¹,

Venkatachalam²,

Masud³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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In current scenario, Wireless Sensor Networks (WSNs) has been applied on variety of applications such as targets tracking, natural resources investigation, monitoring on unapproachable place and so on. Through the sensor nodes, the information for the applications is gathered and transferred. The physical coordination of these sensor nodes is determined, and it is called as localization. The WSN localization methods are studied widely for recent research with the study of small proportion of the sensor node called anchor nodes and their positions are determined through the GPS devices. Sometimes sensor nodes can be a IoT device in the network. With despite this, among the various applications, air pollution and air quality monitoring having many issues on how to place the sensor network in a wide area to monitor the air pollutants level such as carbon dioxide (CO2), nitrogen dioxides (NO2), particulate matter (PM), sulphur dioxide (SO2), ammonia (NH3) and other toxic gases involved in human and industrial activities. The responsibility of the WSN in air quality monitoring is to be positioning the sensor nodes in the large area with low cost and also gather the real time data and produce the monitoring system as an accurate one. In this proposed work, deep learning-based approach called dual graph convolution and LSTM (Long Short-Term Memory) network based (air quality index) AQI predictions were performed. This uses the infrared based technology to measure the CO2, temperature and humidity, Geo statistic method and low power wireless networking. Accuracy of the proposed system is maximum of 95% which is higher than existing techniques.

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“…To measure an individual's pollution footprint, fine granulated air quality monitoring is required. One of the first step by using crowdsourcing for air quality monitoring applications [10] was taken by the project MESSAGE (Mobile Environmental Sensing System Across Grid Environments) from Cambridge University and partners in the UK. They constitute that, low cost components when deployed in high concentrations, can establish a much more precise picture of the spatial and temporal structure of air quality in the urban environment.…”

Section: Related Workmentioning

confidence: 99%

Alcohol Consumption Detection Using Smart Helmet System

Maheswari

Madhumitha

Madhusurya

et al. 2020

IJSRSET

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Internet of Things (IoT) consists of smart devices which can sense the environment and performs the data interaction with the users by handling the large volume of data and also provide the numerous services to the users. It also plays the significant role in Intelligent Transportation System (ITS) using the Cognition ability. One of the primary causes for the road accidents is consumption of alcohol. Driving under the influence (DUI) or Driving While Intoxicated (DWI), and involves operating a vehicle with Blood Alcohol Content (BAC) level of at least 0.08 percent is considered as the punishable offense. In order to identify and prevent the driving with alcohol consumption, the ITS system can be designed with IoT based smart helmet system. The IoT system performs the data validation using the Bayesian Algorithm which significantly detects the alcohol consumption of the rider. And the system also provides the provision to control and ride the bike if and only if the rider does not consume the alcohol.

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Low-Cost Energy-Efficient Air Quality Monitoring System Using Wireless Sensor Network

Cited by 12 publications

References 13 publications

Sistem Monitoring dan Notifikasi Kualitas Udara dalam Ruangan dengan Platform IoT

Sistem Monitoring dan Notifikasi Kualitas Udara dalam Ruangan dengan Platform IoT

Air Pollution Prediction Using Dual Graph Convolution LSTM Technique

Alcohol Consumption Detection Using Smart Helmet System

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