Optimizing agricultural data security: harnessing IoT and AI with Latency Aware Accuracy Index (LAAI)

Area of Science:

• Agricultural Technology
• Data Science
• Cybersecurity

Background:

• Modern agriculture increasingly relies on Internet of Things (IoT) and artificial intelligence (AI) for data-driven operations.
• Ensuring the security and integrity of agricultural data remains a significant challenge despite technological advancements.

Purpose of the Study:

• To introduce a novel evaluation metric, the Latency Aware Accuracy Index (LAAI), for optimizing agricultural data security.
• To address the need for a holistic measure that considers both data accuracy and latency in agricultural data management.

Main Methods:

• Developed the Latency Aware Accuracy Index (LAAI) by integrating capabilities of IoT and AI.
• Incorporated latency as a critical factor in assessing data accuracy and security.

Main Results:

• The LAAI provides a more holistic approach to data accuracy, accounting for latency limitations.
• The metric ensures that farmers receive trustworthy information promptly, enhancing operational efficiency.

Conclusions:

• The LAAI metric enhances agricultural data security and supports informed decision-making for farmers.
• This leads to improved farming practices, contributing to healthier agriculture and greater food security.