Abstract
Achieving food self-sufficiency in hot desert climates requires year-round farming, which is challenging due to extreme weather, water scarcity, and limited arable land. Indoor soil-less farming can mitigate these issues by reducing land and water use but increases operational complexity and electricity needs for cooling, impacting economic sustainability. This paper presents a resource management system using Artificial Intelligence of Things (AIoT) to simplify operations and optimize resources, alongside techno-economic analysis for economic viability. A case study on hydroponic tomato farming in hot deserts demonstrates that beyond a crop yield threshold (24.022 kg/m2), significantly more energy is required for marginal yield increases (e.g., 18% more electricity for a 0.35% yield increase). Despite higher energy use, the techno-economic analysis shows a net present value increase even with unsubsidized electricity. Thus, optimizing energy alongside water and nutrients is crucial for economic sustainability in indoor farming.
| Original language | English |
|---|---|
| Article number | 103958 |
| Journal | Sustainable Energy Technologies and Assessments |
| Volume | 71 |
| DOIs | |
| Publication status | Published - 21 Sept 2024 |
Keywords
- Digital twin
- Genetic optimization
- Indoor farming
- Internet-of-Things
- Resource optimization
- Technoeconomic analysis
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