Farm Vigilance: Smart IoT System for Farmland Monitoring and Animal Intrusion Detection using Neural Network

N, Bhanu K.; B, Sahana K

doi:10.1109/asiancon51346.2021.9544926

Cited by 3 publications

(2 citation statements)

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“…Water scarcity and inefficient irrigation practices present significant challenges to agricultural sustainability [152,[163][164][165][166]. Precision irrigation systems and AI algorithms offer potential solutions to optimize water usage and improve crop yield.…”

Section: Water Management and Irrigation Efficiencymentioning

confidence: 99%

“…These modules are well-suited for applications requiring energy-efficient wireless connectivity, such as environmental monitoring and precision agriculture. Authors such as [139,165] utilized ZigBee modules for farmland monitoring and bee health monitoring. ZigBee technology enables robust communication in challenging agricultural environments, where factors such as interference and power constraints may affect wireless connectivity.…”

Section: Zigbee Modulesmentioning

confidence: 99%

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IoT Solutions with Artificial Intelligence Technologies for Precision Agriculture: Definitions, Applications, Challenges, and Opportunities

Senoo,

Anggraini,

Kumi

et al. 2024

Electronics

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The global agricultural sector confronts significant obstacles such as population growth, climate change, and natural disasters, which negatively impact food production and pose a threat to food security. In response to these challenges, the integration of IoT and AI technologies emerges as a promising solution, facilitating data-driven decision-making, optimizing resource allocation, and enhancing monitoring and control systems in agricultural operations to address these challenges and promote sustainable farming practices. This study examines the intersection of IoT and AI in precision agriculture (PA), aiming to provide a comprehensive understanding of their combined impact and mutually reinforcing relationship. Employing a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we explore the synergies and transformative potential of integrating IoT and AI in agricultural systems. The review also aims to identify present trends, challenges, and opportunities in utilizing IoT and AI in agricultural systems. Diverse forms of agricultural practices are scrutinized to discern the applications of IoT and AI systems. Through a critical analysis of existing literature, this study contributes to a deeper understanding of how the integration of IoT and AI technologies can revolutionize PA, resulting in improved efficiency, sustainability, and productivity in the agricultural sector.

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