AI-Enabled Smart Sprayers in Precision Agriculture: A Sustainability Assessment Through Hilty’s Framework
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- Agriculture represents one of the most impacting sectors from an environmental point of view. The growing global food demand, combined with the depletion of natural resources and the effects of climate change, has made the implementation of newer, more efficient and more sustainable agricultural practices more urgent than ever. In this context, precision agriculture, and AI-enabled smart sprayers within it, have emerged as promising solutions. AI-enabled smart sprayers can optimize the application of agricultural chemicals, such as herbicides and pesticides, reducing waste and pollution while maintaining or improving agricultural productivity. However, it is also important to evaluate the less known consequences of these technologies. These include the materials and energy required to produce and operate their digital components, their disposal as electronic waste, dependence on digital infrastructure and software providers, and possible rebound effects or emerging risks. The current literature provides scattered examples of these impacts but rarely brings them together within a single comprehensive assessment. Therefore, the objective of this thesis is twofold: to understand the environmental benefits generated by AI-enabled smart sprayers, but also to critically analyze, through Hilty’s framework, the environmental burdens and broader sustainability impacts that these technologies may generate but that are sometimes overlooked. AI-enabled smart sprayers were selected as a case study because they represent the intersection of two rapidly developing fields, artificial intelligence and precision agriculture, while focusing on one specific technology makes it possible to conduct a more precise assessment. By analyzing the available literature through the framework proposed by Hilty, this thesis aims to answer the following research questions: “What evidence exists on the positive and negative sustainability impacts of AI-enabled smart sprayers in precision agriculture?” and, subsequently, “Do the environmental benefits of AI-enabled smart sprayers outweigh their environmental burdens?” The thesis is structured as follows. The first part presents the theoretical background, introducing artificial intelligence, precision agriculture, and AI-enabled smart sprayers, including their development, main applications, technical functioning, and wider socioeconomic implications. The second part defines the research scope and objective, describes the methodology of the literature search, and explains Hilty’s framework and its application to this research. The following part applies the framework to AI-enabled smart sprayers by 2. examining their direct, enabling, and systemic effects and gathering the available evidence for each one. The discussion then brings together the findings to assess whether the environmental benefits of these technologies outweigh their environmental burdens. Finally, the thesis acknowledges its limitations and presents its overall conclusions and implications for future research.