Innovative Insights in Computing and Education

Indian Agriculture: Reinventing Agriculture disease identification and crop health management: Agentic AI of Agriculture.   Introduction Indian economy is dependent on agriculture as it boosts the millions of farmers and it also takes a substantial share on the GDP of the country. Crop diseases however have been among the worst fears with the productivity, food security and the incomes of the farmers too. The traditional methods of detecting diseases use manual inspection which is extremely slow, subjective and inaccurate. Growing out of artificial intelligence, more precisely, a new paradigm, called Agentic AI, is now being proposed, which would have intelligent, autonomous and proactive agricultural systems able to detect, diagnose and even cure crop diseases at real-time. The intelligent agents and the possibility to observe the conditions of the environment, analyze information and make a choice and do some actions independently are the substitutes of the reactive struc...

Overview of Agentic AI with A Case Study of Amazon Robotics   What is Agentic AI and Amazon Robotics Case Study.   General overview of Agentic AI. An agentic AI is the ultimate extreme of the idea of artificial intelligence, to shift hypothetically passive and tool-like systems into the role of autonomous and decision-making, thinking things out and acting with minimal human input. In contrast to offering passive action due to the set rules that are already instituted, or reacts to user stimuli, agentic AI systems are thought of in terms of agency. This means that they can perceive the immediate environment, reason their goals, adjust to a changing situation, be proactive in achieving the required outcomes. These systems generally incorporate other AI paradigms of statistical learning, machine learning, natural language processing and symbolic reasoning, to become intelligent agents that can interact with themselves and improve themselves.   Simple Agentic c...

  1. Introduction   Artificial Intelligence (AI) has emerged as a transformative force in modern sports, reshaping how athletes train, recover, prevent injuries, and optimize performance. Unlike traditional sports science methods that rely heavily on manual observations, subjective assessments, and periodic evaluations, AI introduces continuous monitoring, precision analytics, and predictive insights. These capabilities allow sportspersons, coaches, physiotherapists, and medical teams to make faster and more accurate decisions. AI’s integration into sports health is driven by advancements in machine learning, biomechanical modeling, wearable sensor technologies, computer vision, and neurophysiological signal processing. Together, these technologies ensure that athletes remain healthier, recover quicker, and maintain optimal performance throughout intense training cycles and competitive seasons. This article explores five popular AI applications in sportsperson health—injury pr...