Prototipo a pequeña escala de un sistema basado en iot para controlar cultivos en entornos urbanos
In recent years, the population has witnessed an exponential growth, which presents the challenge of satisfying the growing food demand. This has led to the necessity of innovating in the field of urban agriculture. In this context, 'AgriUrbTech,' an IoT-based system designed to enhance th...
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| フォーマット: | bachelorThesis |
| 言語: | spa |
| 出版事項: |
2024
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| 主題: | |
| オンライン･アクセス: | https://repositorio.uteq.edu.ec/handle/43000/7222 |
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タグ追加 | 要約: | In recent years, the population has witnessed an exponential growth, which presents the challenge of satisfying the growing food demand. This has led to the necessity of innovating in the field of urban agriculture. In this context, 'AgriUrbTech,' an IoT-based system designed to enhance the control and monitoring of crops in urban environments, has been developed, applying the TDDM4IoTS methodology, which is ideal for working with IoT technologies. This automation facilitates the proper management of water and time resources, promoting sustainable practices and the productivity of urban crops. The implementation of rule-based decisions and pest recognition through machine learning models are innovative features of the system that support informed decision-making and improve crop management. Additionally, the yield per harvest has notably increased, showing a 68.42% improvement compared to traditional methods, demonstrating the system's capability not only to efficiently manage resources but also to significantly boost production. The acceptability assessment among real users, involving a total of 12 participants, revealed a positive perception, emphasizing high utility (90.74%), ease of use (73.36%), and a favorable attitude towards its usage (94.47%). These outcomes highlight AgriUrbTech's effectiveness in real settings and its potential to enhance urban agriculture. This work contributes to the technological advancement in agriculture, proposing ways for the expansion and efficiency of these practices in the urban context. Future research could explore the integration of other emerging technologies and data analytics for even more effective resource management in urban agriculture. |
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