Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing
Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather st...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/22/9060 |
| _version_ | 1797457794852454400 |
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| author | Antonio Rivera Pedro Ponce Omar Mata Arturo Molina Alan Meier |
| author_facet | Antonio Rivera Pedro Ponce Omar Mata Arturo Molina Alan Meier |
| author_sort | Antonio Rivera |
| collection | DOAJ |
| description | Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors. |
| first_indexed | 2024-03-09T16:28:05Z |
| format | Article |
| id | doaj.art-0822fa3725e44470bdd1d2382a690538 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T16:28:05Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0822fa3725e44470bdd1d2382a6905382023-11-24T15:05:11ZengMDPI AGSensors1424-82202023-11-012322906010.3390/s23229060Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data SharingAntonio Rivera0Pedro Ponce1Omar Mata2Arturo Molina3Alan Meier4Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 14380, MexicoInstitute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 14380, MexicoInstitute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 14380, MexicoInstitute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 14380, MexicoLawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USACurrent weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.https://www.mdpi.com/1424-8220/23/22/9060weather analyticssustainable monitoringatmospheric datapredictive modelingdata collaborationsensor networks |
| spellingShingle | Antonio Rivera Pedro Ponce Omar Mata Arturo Molina Alan Meier Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing Sensors weather analytics sustainable monitoring atmospheric data predictive modeling data collaboration sensor networks |
| title | Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing |
| title_full | Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing |
| title_fullStr | Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing |
| title_full_unstemmed | Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing |
| title_short | Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing |
| title_sort | local weather station design and development for cost effective environmental monitoring and real time data sharing |
| topic | weather analytics sustainable monitoring atmospheric data predictive modeling data collaboration sensor networks |
| url | https://www.mdpi.com/1424-8220/23/22/9060 |
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