IoT and fuzzy logic integration for improved substrate environment management in mushroom cultivation

Irwanto, Firdaus; Hasan, Umar; Lays, Eric Saputra; De La Croix, Ntivuguruzwa Jean; Mukanyiligira, Didacienne; Sibomana, Louis; Ahmad, Tohari

doi:10.1016/j.atech.2024.100427

Smart Agricultural Technology

2024

DOI: 10.1016/j.atech.2024.100427

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IoT and fuzzy logic integration for improved substrate environment management in mushroom cultivation

Firdaus Irwanto,

Umar Hasan,

Eric Saputra Lays

et al.

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Cited by 2 publications

References 40 publications

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A comprehensive review to evaluate the synergy of intelligent food packaging with modern food technology and artificial intelligence field

Abekoon,

Buthpitiya,

Sajindra

et al. 2024

Discov Sustain

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This study reviews recent advancements in food science and technology, analyzing their impact on the development of intelligent food packaging within the complex food supply chain. Modern food technology has brought about intelligent food packaging, which includes sensors, indicators, data carriers, and artificial intelligence. This innovative packaging helps monitor food quality and safety. These innovations collectively aim to establish an unbroken chain of food safety, freshness, and traceability, from production to consumption. This research explores the components and technologies of intelligent food packaging, focusing on key indicators like time–temperature indicators, gas indicators, freshness indicators, and pathogen indicators to ensure optimal product quality. It further incorporates various types of sensors, including gas sensors, chemical sensors, biosensors, printed electronics, and electronic noses. It integrates data carriers such as barcodes and radio-frequency identification to enhance the complexity and functionality of this system. The review emphasizes the growing influence of artificial intelligence. It looks at new advances in artificial intelligence that are driving the development of intelligent packaging, making it better at preserving food freshness and quality. This review explores how modern food technologies, especially artificial intelligence integration, are revolutionizing intelligent packaging for food safety, quality, reduced waste, and enhanced traceability.

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A comprehensive review to evaluate the synergy of intelligent food packaging with modern food technology and artificial intelligence field

Abekoon,

Buthpitiya,

Sajindra

et al. 2024

Discov Sustain

View full text Add to dashboard Cite

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Organized Optimization Integration Validation Model for Internet of Things (IoT)-Based Real-Time Applications

Alghuried,

Alghuson,

Alahmari

et al. 2024

Mathematics

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Emerging technology like the Internet of Things (IoT) has great potential for use in real time in many areas, including healthcare, agriculture, logistics, manufacturing, and environmental surveillance. Many obstacles exist alongside the most popular IoT applications and services. The quality of representation, modeling, and resource projection is enhanced through interactive devices/interfaces when IoT is integrated with real-time applications. The architecture has become the most significant obstacle due to the absence of standards for IoT technology. Essential considerations while building IoT architecture include safety, capacity, privacy, data processing, variation, and resource management. High levels of complexity minimization necessitate active application pursuits with variable execution times and resource management demands. This article introduces the Organized Optimization Integration Validation Model (O2IVM) to address these issues. This model exploits k-means clustering to identify complexities over different IoT application integrations. The harmonized service levels are grouped as a single entity to prevent additional complexity demands. In this clustering, the centroids avoid lags of validation due to non-optimized classifications. Organized integration cases are managed using centroid deviation knowledge to reduce complexity lags. This clustering balances integration levels, non-complex processing, and time-lagging integrations from different real-time levels. Therefore, the cluster is dissolved and reformed for further integration-level improvements. The volatile (non-clustered/grouped) integrations are utilized in the consecutive centroid changes for learning. The proposed model’s performance is validated using the metrics of execution time, complexity, and time lag.

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IoT and fuzzy logic integration for improved substrate environment management in mushroom cultivation

Cited by 2 publications

References 40 publications

A comprehensive review to evaluate the synergy of intelligent food packaging with modern food technology and artificial intelligence field

A comprehensive review to evaluate the synergy of intelligent food packaging with modern food technology and artificial intelligence field

Organized Optimization Integration Validation Model for Internet of Things (IoT)-Based Real-Time Applications

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