Grow Ease: The Smart and Ultimate Solution for Home Gardening
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2025
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| _version_ | 1866901528441257984 |
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| author | Aarjav Jain1 ,Harsh Kumar Singh2 ,Hritik Kumar3,Bhupesh Kumar Gupta4 ,Himanshu Chaudhary5 |
| author_facet | Aarjav Jain1 ,Harsh Kumar Singh2 ,Hritik Kumar3,Bhupesh Kumar Gupta4 ,Himanshu Chaudhary5 |
| contents | <p>Indoor gardening faces several challenges, including inconsistent care practices, pest infestations, and environmental<br>mismanagement. Grow Ease, a new web application developed using artificial intelligence (AI), the Internet of Things<br>(IoT), and MongoDB, successfully addresses these issues by providing personalized solutions for plant care. This paper<br>describes the development, operation, and impact of Grow Ease, demonstrating a 40% increase in plant survival and a 35%<br>reduction in user error as indicated by beta testing (n=200). Major enhancements include adaptive scheduling, plant<br>identification using convolutional neural networks (CNN) with 92% accuracy, and IoT sensor integration. The app<br>promotes sustainability by saving water resources and minimizing wastage of plants, while its ease of use allows it to be<br>operated by users at different levels of expertise. Future expansions include IoT-enabled smart pots and community-driven<br>knowledge sharing.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17763223 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Grow Ease: The Smart and Ultimate Solution for Home Gardening Aarjav Jain1 ,Harsh Kumar Singh2 ,Hritik Kumar3,Bhupesh Kumar Gupta4 ,Himanshu Chaudhary5 Indoor gardening, AI-driven solutions, MongoDB, IoT, sustainable horticulture <p>Indoor gardening faces several challenges, including inconsistent care practices, pest infestations, and environmental<br>mismanagement. Grow Ease, a new web application developed using artificial intelligence (AI), the Internet of Things<br>(IoT), and MongoDB, successfully addresses these issues by providing personalized solutions for plant care. This paper<br>describes the development, operation, and impact of Grow Ease, demonstrating a 40% increase in plant survival and a 35%<br>reduction in user error as indicated by beta testing (n=200). Major enhancements include adaptive scheduling, plant<br>identification using convolutional neural networks (CNN) with 92% accuracy, and IoT sensor integration. The app<br>promotes sustainability by saving water resources and minimizing wastage of plants, while its ease of use allows it to be<br>operated by users at different levels of expertise. Future expansions include IoT-enabled smart pots and community-driven<br>knowledge sharing.</p> |
| title | Grow Ease: The Smart and Ultimate Solution for Home Gardening |
| topic | Indoor gardening, AI-driven solutions, MongoDB, IoT, sustainable horticulture |
| url | https://doi.org/10.5281/zenodo.17763223 |