A comprehensive review on the use of artificial intelligence, internet of things, sensors, and green energy in non-invasive agricultural techniques

Feeding a burgeoning global population amid cli mate change and dwindling resources presents a profound chal lenge for agriculture. This paper examines ”smart agriculture” (Agriculture 4.0) as a pivotal solution, integrating technologies like IoT, AI, and robotics to cultivate data-driven, efficient, and sustainable farming. We emphasize the growing effectiveness of multi-modal data fusion—combining diverse sensor inputs—for improved pest detection, water management, and yield predic tion. A critical shift towards decentralized edge intelligence is also explored, facilitating real-time, on-farm decisions and overcoming connectivity hurdles. While acknowledging that successful implementations are highly context-specific and that synthetic data can address scarcity, we also confront persistent obstacles: high adoption costs, the digital divide, unreliable rural connectivity, and cybersecurity risks. Ultimately, realizing smart agriculture’s full potential—a more resilient and productive global food system—requires sustained investment in affordable sensors, robust and explainable AI, and autonomous robotics to translate data insights into actionable field-level strategies.