Using Arduino Iot Modules As A Low Cost Environmental Research Monitoring System
Environmental monitoring plays a crucial role in understanding the impact of human activities on our ecosystems. However, the cost and complexity of traditional monitoring systems often hinder widespread deployment, especially in resource-constrained regions. This research paper explores the feasibi...
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| Published in: | 2023 International Conference on Computer Science and Emerging Technologies (CSET) pp. 1 - 6 |
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| Main Authors: | , , , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
10.10.2023
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| Abstract | Environmental monitoring plays a crucial role in understanding the impact of human activities on our ecosystems. However, the cost and complexity of traditional monitoring systems often hinder widespread deployment, especially in resource-constrained regions. This research paper explores the feasibility and effectiveness of employing Arduino Internet of Things (IoT) modules as a low-cost alternative for environmental research monitoring. The study focuses on designing and implementing an Arduino-based environmental monitoring system capable of gathering real-time data on key environmental parameters, such as temperature, humidity, air quality, and soil moisture. The hardware setup comprises Arduino microcontrollers interfaced with a range of environmental sensors and connectivity modules for data transmission. To assess the system's reliability and accuracy, a series of field experiments were conducted in diverse environmental settings, including urban areas, agricultural zones, and natural habitats. The collected data was compared against measurements from conventional monitoring equipment to validate the Arduino-based system's performance. The research demonstrates that the Arduino IoT modules can effectively monitor and transmit environmental data with a reasonable level of accuracy and stability, making them suitable for various environmental research applications. The low-cost nature of Arduino components and the open-source ecosystem facilitate customization and scalability, enabling researchers and organizations to develop tailored monitoring solutions for specific environmental contexts. Additionally, the paper discusses the challenges and limitations encountered during the deployment of Arduino-based monitoring systems, including power constraints, sensor calibration, and data processing techniques. Furthermore, it explores potential avenues for improvement and optimization to enhance the system's capabilities and data accuracy. In conclusion, this research highlights the practicality and promise of using Arduino IoT modules as a low-cost environmental research monitoring system. By presenting a viable alternative to expensive and complex monitoring solutions, the study opens up opportunities for researchers, environmentalists, and policymakers to establish cost-effective monitoring networks and gather essential data for informed decision-making, ultimately contributing to more sustainable and eco-friendly practices. |
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| AbstractList | Environmental monitoring plays a crucial role in understanding the impact of human activities on our ecosystems. However, the cost and complexity of traditional monitoring systems often hinder widespread deployment, especially in resource-constrained regions. This research paper explores the feasibility and effectiveness of employing Arduino Internet of Things (IoT) modules as a low-cost alternative for environmental research monitoring. The study focuses on designing and implementing an Arduino-based environmental monitoring system capable of gathering real-time data on key environmental parameters, such as temperature, humidity, air quality, and soil moisture. The hardware setup comprises Arduino microcontrollers interfaced with a range of environmental sensors and connectivity modules for data transmission. To assess the system's reliability and accuracy, a series of field experiments were conducted in diverse environmental settings, including urban areas, agricultural zones, and natural habitats. The collected data was compared against measurements from conventional monitoring equipment to validate the Arduino-based system's performance. The research demonstrates that the Arduino IoT modules can effectively monitor and transmit environmental data with a reasonable level of accuracy and stability, making them suitable for various environmental research applications. The low-cost nature of Arduino components and the open-source ecosystem facilitate customization and scalability, enabling researchers and organizations to develop tailored monitoring solutions for specific environmental contexts. Additionally, the paper discusses the challenges and limitations encountered during the deployment of Arduino-based monitoring systems, including power constraints, sensor calibration, and data processing techniques. Furthermore, it explores potential avenues for improvement and optimization to enhance the system's capabilities and data accuracy. In conclusion, this research highlights the practicality and promise of using Arduino IoT modules as a low-cost environmental research monitoring system. By presenting a viable alternative to expensive and complex monitoring solutions, the study opens up opportunities for researchers, environmentalists, and policymakers to establish cost-effective monitoring networks and gather essential data for informed decision-making, ultimately contributing to more sustainable and eco-friendly practices. |
| Author | Kumar, Rohit Marie, Ziyad Bin Ibrahim, Mohd Hafizuddin Jusoh, Julaily Aida Magableh, Murad Mohamed, Rajina R. |
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| Snippet | Environmental monitoring plays a crucial role in understanding the impact of human activities on our ecosystems. However, the cost and complexity of... |
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| SubjectTerms | Arduino Microcontrollers Costs Ecosystems Internet of Things IoT Low-Cost Environmental Monitoring System Sensors Temperature distribution Temperature measurement Temperature sensors Urban areas |
| Title | Using Arduino Iot Modules As A Low Cost Environmental Research Monitoring System |
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