Challenges of Implementing Internet of Things-Based Technologies in Agricultural Water Management

ABSTRACT

The exacerbating water crisis and the inefficiency of conventional water management models in the agricultural sector have made the adoption of IoT-based technologies a necessity for optimal water resource management. This study was conducted to analyze the challenges of implementing IoT-based water management technologies in the agricultural sector of Kermanshah province. The statistical population consisted of specialists and experts in the fields of IoT, water, and agriculture, from which 151 individuals were randomly selected and studied. The face and content validity of the questionnaire were confirmed using expert opinions, and its discriminant validity was verified using the average variance extracted index. The reliability of the questionnaire was also assessed through Cronbach's alpha and composite reliability. Data analysis was performed using SPSS v.26 and SmartPLS v.3. The results of ranking the challenges using the coefficient of variation revealed that the mismatch between the cost of these technologies and the farmers' financial capacity, the massive volume of data requiring advanced processing infrastructure, and limited access to credit facilities are the most significant challenges facing the use of IoT in agricultural water management. Furthermore, based on the confirmatory factor analysis results, economic challenges (0.895) constituted the greatest obstacle to IoT technology implementation, followed by technical (0.879), policy-legal (0.806), social (0.8), infrastructural (0.778), and environmental (0.508) challenges, respectively. Overcoming these challenges necessitates designing financing mechanisms, developing indigenous data processing and analysis platforms, enhancing communication infrastructure, building human capacity, and establishing clear legal frameworks for the successful implementation of IoT in agricultural water management.





EXTENDED ABSTRACT

Context and Purpose

The intensifying water crisis in Iran has rendered the transformation from traditional water management to smart, data-driven systems in agriculture an inevitable necessity. This study aimed to identify, validate, and prioritize the challenges of implementing Internet of Things (IoT)-based technologies for agricultural water management in Kermanshah Province, Iran. The research specifically sought to develop and test a comprehensive multi-dimensional model of these challenges through Confirmatory Factor Analysis (CFA), providing a theoretical framework and practical roadmap for stakeholders.



Research Methodology

This quantitative, applied research adopted a survey methodology. The statistical population consisted of experts in IoT, water, and agriculture in Kermanshah Province, including university faculty, researchers, and relevant government and private sector specialists. Using power analysis (Cohen, 1988), a sample size of 161 was determined; ultimately, 151 valid questionnaires were collected via simple random sampling. The data collection instrument was a questionnaire developed through an extensive literature review of Persian and English sources. The questionnaire categorized potential challenges into six latent constructs: Economic, Technical, Policy-Legal, Social, Infrastructural, and Environmental. Items were measured on a five-point Likert scale. Content validity was confirmed by a panel of experts, and discriminant validity was assessed using Average Variance Extracted (AVE). Reliability was confirmed with Cronbach's alpha and composite reliability scores, all exceeding 0.7. Data analysis was performed using SPSS 26 for descriptive statistics and Smart PLS 3 for Structural Equation Modeling (SEM), specifically Confirmatory Factor Analysis (CFA).



Findings

The descriptive findings indicated a consensus among experts on several key challenges. The lowest coefficient of variation (CV) was observed for the "Mismatch between technology costs and farmers' financial capacity" (Economic), highlighting its perceived centrality. In the infrastructural dimension, "Lack of IoT demonstration farms" had the lowest CV. CFA results validated the proposed six-factor structure, explaining a significant portion of the variance in implementation challenges. The standardized path coefficients revealed the following order of importance for the latent constructs:

1. Economic challenges (β = 0.895): Identified as the most significant barrier, encompassing high investment costs, limited access to credit, and insufficient R&D funding.

2. Technical challenges (β = 0.879): The second major barrier, including issues related to big data management, processing needs, hardware vulnerability, and energy supply.

3. Policy and legal challenges (β = 0.806): Encompassing the lack of a national strategic plan, ambiguous data ownership laws, and insufficient equipment standards.

4. Social challenges (β = 0.800): Involving low trust in technology, cultural resistance to change, and a lack of specialized training for farmers.

5. Infrastructural challenges (β = 0.778): Including weak internet connectivity in rural areas and a shortage of local technical support services.

6. Environmental challenges (β = 0.508): Although recognized, these were considered a lower-priority concern in the short term, relating to the ecological footprint of electronic waste and energy consumption.



Conclusion

The successful implementation of IoT-based water management technologies in Kermanshah Province is hindered by a complex, interconnected web of challenges across six dimensions. A purely technological or top-down approach is insufficient. An effective strategy requires a systemic, multi-pronged policy intervention. This must prioritize economic interventions, such as tailored financial schemes and cooperative procurement models, to alleviate the primary cost barrier. Simultaneously, it must address technical bottlenecks by fostering the development of local data platforms and maintenance ecosystems. Foundational to these efforts is the establishment of a clear policy-legal framework, including a provincial smart agriculture roadmap and regulations for data governance. Complementary actions are needed to build social trust through demonstration farms and farmer organizations, and to close the digital divide by improving rural connectivity and energy access. A cross-sectoral steering committee is recommended to coordinate these integrated efforts, ensuring that the transition to smart water management enhances agricultural productivity, sustainability, and resilience in the face of Iran's pressing water crisis.