Precision Irrigation and Smart Greenhouse Technologies for Sustainable Agriculture: An Integrated Review
B. Sarojini Devi, E. Manjunatha
Journal of Scientific Research and Reports · pp. 539–555 · Published 14 Mar 2026
10.9734/jsrr/2026/v32i34068Abstract
Sustainable agriculture faces a dual constraint that is becoming increasingly structural rather than episodic: water scarcity and climate volatility on the one hand, and rising expectations for stable yields, quality, and environmental performance on the other. Precision irrigation and smart greenhouse technologies have emerged as two complementary pathways for addressing these constraints by shifting water and climate management from periodic, experience-driven actions to continuous, sensor-informed, and algorithmically supported decisions. This review synthesises research from 2000–2026 on the technical foundations, decision architectures, and sustainability outcomes of precision irrigation and smart greenhouse systems, with particular emphasis on how these domains converge through shared advances in sensing, connectivity, modelling, and control. The review traces the evolution from soil- and weather-based irrigation scheduling towards multi-source monitoring frameworks, decision support systems, and advanced control strategies, and it examines the parallel transition in protected cultivation from conventional environmental control to data-driven controlled environment agriculture. The analysis highlights enabling technologies such as wireless sensor networks, remote sensing of evapotranspiration, unmanned aerial systems, Internet of Things platforms, and open models for greenhouse energy–climate interactions. It also evaluates reported impacts on water productivity, energy demand, and operational resilience, while identifying persistent barriers in interoperability, data quality, cost, and skills. The paper concludes that the next phase of innovation is likely to be defined by integrated “water–energy–climate” optimisation across field and greenhouse contexts, supported by transparent decision support, robust control, and verifiable sustainability metrics.
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