TY - JOUR
T1 - IoT and fuzzy logic integration for improved substrate environment management in mushroom cultivation
AU - Irwanto, Firdaus
AU - Hasan, Umar
AU - Lays, Eric Saputra
AU - De La Croix, Ntivuguruzwa Jean
AU - Mukanyiligira, Didacienne
AU - Sibomana, Louis
AU - Ahmad, Tohari
N1 - Publisher Copyright:
© 2024
PY - 2024/3
Y1 - 2024/3
N2 - The current era witnesses the advent of the Internet of Things (IoT), a transformative force giving rise to various technological innovations, most notably connected objects. This paradigm shift catalyzes the widespread adoption of autonomous decision-making systems, particularly in sectors like agriculture, where the aim is to amplify productivity. As a result of the agricultural domain, mushrooms have concurrently emerged as a significant component of daily diets, offering additional vitamins and flavor. Despite their popularity, cultivating mushrooms in open environments poses challenges in maintaining optimal environmental conditions, prompting numerous research efforts. Recognizing the inconsistencies in existing approaches to safeguard vital parameters in mushroom farms, this paper introduces an innovative system utilizing intelligent sensors whose real-time records are managed based on the fuzzy sets concept. These sensors, encompassing the Capacitive Soil Moisture Sensor v1.2, DHT22 Sensor, Light Dependent Resistor (LDR sensor), and Passive Infrared Receiver (PIR sensor), collectively capture essential data for decision-making in mushroom farming. Employing fuzzy logic, the system addresses pivotal aspects such as substrate watering, environmental control, light management, and pest detection. Through experimental results, it becomes evident that the proposed system not only exemplifies the potential of IoT technologies in agriculture but also offers a comprehensive and efficient approach to real-time decision-making. By aggregating sensor data, the system proves instrumental in enhancing the quality and yield of mushroom crops, showcasing a promising trajectory for sustainable and technologically driven agricultural practices.
AB - The current era witnesses the advent of the Internet of Things (IoT), a transformative force giving rise to various technological innovations, most notably connected objects. This paradigm shift catalyzes the widespread adoption of autonomous decision-making systems, particularly in sectors like agriculture, where the aim is to amplify productivity. As a result of the agricultural domain, mushrooms have concurrently emerged as a significant component of daily diets, offering additional vitamins and flavor. Despite their popularity, cultivating mushrooms in open environments poses challenges in maintaining optimal environmental conditions, prompting numerous research efforts. Recognizing the inconsistencies in existing approaches to safeguard vital parameters in mushroom farms, this paper introduces an innovative system utilizing intelligent sensors whose real-time records are managed based on the fuzzy sets concept. These sensors, encompassing the Capacitive Soil Moisture Sensor v1.2, DHT22 Sensor, Light Dependent Resistor (LDR sensor), and Passive Infrared Receiver (PIR sensor), collectively capture essential data for decision-making in mushroom farming. Employing fuzzy logic, the system addresses pivotal aspects such as substrate watering, environmental control, light management, and pest detection. Through experimental results, it becomes evident that the proposed system not only exemplifies the potential of IoT technologies in agriculture but also offers a comprehensive and efficient approach to real-time decision-making. By aggregating sensor data, the system proves instrumental in enhancing the quality and yield of mushroom crops, showcasing a promising trajectory for sustainable and technologically driven agricultural practices.
KW - Fuzzy logic
KW - Internet of things
KW - Mushroom farming
KW - National food security
KW - Smart agriculture
KW - Smart sensors
UR - http://www.scopus.com/inward/record.url?scp=85186978742&partnerID=8YFLogxK
U2 - 10.1016/j.atech.2024.100427
DO - 10.1016/j.atech.2024.100427
M3 - Article
AN - SCOPUS:85186978742
SN - 2772-3755
VL - 7
JO - Smart Agricultural Technology
JF - Smart Agricultural Technology
M1 - 100427
ER -