Forschungsarbeit, 2013
5 Seiten
1. INTRODUCTION
2. System Overview
2.1 Proposed System
2.2 Hardware Architecture
2.2.1. ATMEGA16 microcontroller
2.2.2. Sensors Array
2.2.3. ZigBee Modules
2.3.4. Central Server
3. ZigBee Standard
4. AIR Quality
4.1 Carbon Dioxide (CO2)
4.2 Sulphur Dioxide (SO2)
4.3 Nitrogen Dioxide (NO2)
4.4 Air-Quality-Index
5. Conclusion
The primary objective of this work is to design and implement a cost-effective, low-power Wireless Sensor Network (WSN) system for real-time air pollution monitoring, enabling the government to categorize environmental pollutant levels efficiently.
1. INTRODUCTION
Air pollution is one of the most important factors affecting the quality of life and the health of the increasingly urban population of industrial societies. In many cities, the air is polluted by emissions from sources such as cars and trucks, power plants, and manufacturing processes. When gases and particles from those activities accumulate in the air in high enough concentrations, they can be harmful for human health, an environment. Often, terrain and meteorological conditions complicate air quality issues in the area. Although the national trend is toward better outdoor air quality, there are some urban areas in which no improvement has taken place. Concentrations of outdoor air pollutants vary from day-to-day and even during the course of a day.
For health protection, the public needs timely information about air quality and other factors (e.g., weather conditions) that affect it. An access to air quality forecasts allows residents to reduce their exposure when the pollutant concentrations are high. This is important particularly to people who are sensitive to certain pollutants’ harmful effects. For example, people with asthma may be sensitive to ground level ozone and sulphur dioxide. The major motivation behind our study and the development of the system is to help the government to devise an indexing system to categories air pollution in India. The project is to build an air pollution monitoring system, so a detection system for multiple information of environment is designed in this project.
1. INTRODUCTION: Discusses the significance of air pollution on human health and the limitations of current passive or manual monitoring systems.
2. System Overview: Details the proposed WSN architecture, hardware components including ATMEGA16 microcontrollers, sensor arrays, and ZigBee communication modules.
3. ZigBee Standard: Explains the IEEE 802.15.4 based wireless networking technology used for low-power, short-range data transmission in the system.
4. AIR Quality: Provides an overview of atmospheric pollutants and the methodology for calculating the Air Quality Index (AQI) based on specific gas concentrations.
5. Conclusion: Summarizes the successful implementation of the WSN system and its ability to provide actionable data to authorities through real-time monitoring.
Air Pollution, AtMega16 microcontroller, MG811 Sensor, MQ6 Sensor, MQ135 Sensor, Real Time, ZigBee, WSN, Air Quality Index, Gas Monitoring, Wireless Sensor Network, Environmental Protection, Data Aggregation.
The paper focuses on designing a cost-effective and low-power Wireless Sensor Network (WSN) to perform real-time monitoring of atmospheric pollutants in urban environments.
The core themes include wireless sensor technology, air quality management, gas sensing hardware, and communication protocols based on the IEEE 802.15.4 standard.
The goal is to develop a robust system capable of providing continuous, real-time data on hazardous gases (CO2, NO2, SO2) to help government authorities categorize pollution levels.
The authors use an engineering approach involving system design, sensor hardware integration, and the deployment of ZigBee modules to establish a mesh-capable communication network.
The main body details the hardware architecture, the selection of gas sensors, the logic behind the Air Quality Index (AQI) formula, and the configuration of the network stack.
Key terms include WSN, ZigBee, Air Quality Index (AQI), ATMEGA16, and real-time gas monitoring.
The AQI is derived by dividing the measured raw pollutant level by the established pollutant standard for a specific region and multiplying the result by 100.
ZigBee modules are chosen because they offer lower cost, lower power consumption, and simpler installation and maintenance compared to the more complex GSM or GPRS networks.
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