Development of IoT-Based Compact Mushroom Cultivation Monitoring System
Development of an IoT-Based Compact Mushroom Cultivation System (CMCS) project integrates advanced Internet of Things (IoT) technology with traditional mushroom cultivation practices to address challenges enthusiasts, small-scale farmers, and researchers face. CMCS aims to create an intelligent cultivation environment that accurately controls important environmental factors like temperature and humidity to optimize the conditions for mushroom growth. This project aligns with Sustainable Development Goal (SDG) 2, which seeks to eliminate hunger, achieve food security, improve nutrition, and adopt sustainable agriculture. The compact system will be outfitted with an Internet of Things (IoT) based automatic control system that can regulate temperature and humidity fluctuations in the environment. This system will include the Raspberry Pi 4, Arduino UNO, DHT22 sensor, LDR sensor, relays, Node-Red, and MQTT Dashboard. Together, these elements create a comprehensive structure that allows for the real-time monitoring and control of the cultivation environment. The data gathered from the system undergoes processing and analysis using a cloud-based platform, which offers real-time insights and control through a user-friendly interface. This study investigates the creation and execution of the system, emphasizing the difficulties faced and the strategies developed to overcome them. The implementation of CMCS promises to transform conventional mushroom farming through its ability to offer accurate and immediate monitoring and control, resulting in improved efficiency and long-term viability. In addition, it also supports sustainable agricultural practices, which are in line with the broader goals of SDG 2.
Authors
- Mokhtar Hashim
- Nor Sukor Ali
- Shaizan Bin Jusoh
- Noor Ropidah Bujal
- Syazana Md Dali
- Mohamed Noor Azman Bidin
Institutions
- Sultan Haji Ahmad Shah Hospital (MY)
Publication Details
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1109/gis-ideas63212.2024.10991207
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.60