Data

Real time soil moisture data and weather data

Central Queensland University
Varun Yarehalli Chandrappa (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25946/29670476.v1&rft.title=Real time soil moisture data and weather data&rft.identifier=10.25946/29670476.v1&rft.publisher=Central Queensland University&rft.description=The objective of the proposed research is to develop an IoT based intelligent watering system in the managed parks. This objective is aligned with CQUniversity's research strength under the area: “smart systems and computational intelligence”. In this project, we will install several data collection sensors to monitor the moisture content of the park. Some of these data collection sources will be automated for real-time collection and storing of data in a cloud storage facility. This information will be used with data mining technologies to analyse for accurate watering and forecasting. The decision of the developed model will be integrated with the existing irrigation systems for smart automation, which will deliver water in accordance with the requirements of the plant, the rainfall received and evaporative demand of the system. The skills which we are going to learn while doing this project is machine learning, artificial intelligence, IoT and programming skills.&rft.creator=Varun Yarehalli Chandrappa&rft.date=2025&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_subject=Semi- and unsupervised learning&rft_subject=Software architecture&rft_subject=Programming languages&rft_subject=Machine learning not elsewhere classified&rft_subject=Intelligent&rft_subject=Fresh, ground and surface water systems and management&rft.type=dataset&rft.language=English Access the data

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The objective of the proposed research is to develop an IoT based intelligent watering system in the managed parks. This objective is aligned with CQUniversity's research strength under the area: “smart systems and computational intelligence”. In this project, we will install several data collection sensors to monitor the moisture content of the park. Some of these data collection sources will be automated for real-time collection and storing of data in a cloud storage facility. This information will be used with data mining technologies to analyse for accurate watering and forecasting. The decision of the developed model will be integrated with the existing irrigation systems for smart automation, which will deliver water in accordance with the requirements of the plant, the rainfall received and evaporative demand of the system. The skills which we are going to learn while doing this project is machine learning, artificial intelligence, IoT and programming skills.

Data time period: 2020-03-07 to 2022-03-07

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