Investigating The Indicators and Feasibility of Creating a Smart Village (Case Study: Hamedan County)

Introduction

Over the past decade, the expansion of information and smart technologies has significantly impacted the development and enhancement of infrastructure and the quality of life in rural communities. With increasing migration from rural areas to cities and challenges such as environmental crises and resource limitations, empowering policies and sustainable approaches to rural life have garnered more attention. The smartization approach, utilizing advanced technologies like the Internet of Things and digital solutions, aims to improve productivity, comfort, and residents quality of life requiring attention to local differences and intelligent resource management. This process, however, faces challenges such as infrastructural, economic, and educational constraints. Nonetheless, the roles of governments, active community participation, and human capacity development can facilitate the realization of smart village development goals. In this study, by leveraging international experiences and developing relevant indicators, the alignment of villages in Hamadan County with smart village criteria was evaluated. Through quantitative analysis based on 384 questionnaires and using SPSS software, the current status was identified, and strategies for improving these communities were explored.
 

Methodology

The methodology of this study is based on a quantitative approach and objective data analysis. In the first stage, relevant indicators related to the concept of a smart village were developed by reviewing reference studies and documentary sources, taking into account regional conditions and characteristics. Subsequently, to validate the indicators, expert opinions from rural development specialists were utilized, and through refinement and integration of their perspectives, the final set of indicators was designed. The data collection tool was a structured questionnaire developed based on these indicators. Content and face validity of the questionnaire were confirmed by relevant experts, and its reliability, measured using Cronbach's alpha test, yielded a value above 0.7, indicating the tool’s dependability. Furthermore, the variables’ randomness and the normality of the data distribution were verified using the Kolmogorov-Smirnov test, with a coefficient of 0.878, confirming data normality. Finally, to assess the status of smartness indicators in the area from four perspectives environmental, social, economic, and institutional—one-sample t-tests  and one-way Anova were employed.
 

Findings

The results of the one-sample t-test indicated that the indicators of the smart village are in a relatively unfavorable condition. The social dimension is comparatively better than other aspects, especially in the field of education, where the development of virtual training and digital technologies has led to a relatively favorable situation. However, the health and safety indicator is in an unsatisfactory state and requires improvements in technology infrastructure and training. The institutional and planning indicators also show weaknesses and need comprehensive policies, structural reforms, and strengthened collaboration among various organizations. Additionally, the analysis highlights that local, economic, and social factors play a significant role in the development of smart villages, and achieving this goal necessitates comprehensive cooperation and the utilization of successful experiences from other countries.The results of the one-sample t-test indicated that the environmental dimension indicators have a mean score of 2.92, with confidence intervals both negative, reflecting an undesirable and poor condition. In contrast, findings for the social dimension were different. This dimension, assessed through four indicators—education, health and safety, security, and capability—showed that three indicators (education with a mean of 3.13, security with a mean of 3.23, and capability with a mean of 3.11) are considered favorable, while the health and safety indicator (mean of 2.87) is evaluated as unfavorable. For analyzing the economic indicators of the smart village in the region, two factors—agriculture and services—were used. The agriculture indicator had a mean score of 2.82, and the services indicator was at 2.43, both in an undesirable state. Finally, the status of institutional indicators in the region had a mean of 2.54, which also reflects an unfavorable condition for the smart village.
 

Discussion and Conclusion

The computed averages indicate that the conditions of the indicators for the smart village in the studied area are not in a favorable state. Specifically, in the environmental dimension, the indicators for environment, energy, and infrastructure of the studied villages are all assessed as unfavorable. The environmental index has an average of 3.20, suggesting a relatively good condition; however, energy (2.75) and infrastructure (2.82) indicators, considering their significance levels and the negative upper and lower bounds, reflect poor conditions and notable deficiencies in these areas. Overall, the environmental indicators’ average of 2.92 emphasizes the poor state and the need for ongoing improvements in environmental, energy, and infrastructure sectors.Additionally, the analysis shows that the social situation of villages in Hamadan County is also not in an optimal condition. The education index, with an average of 3.13; safety with 3.23; and capability with 3.11—all indicate a relatively adequate situation but still require strengthening. Among the educational aspects, the use of social applications for skill enhancement and online training has been positively evaluated, but the overall education level and effective use of educational technologies need further development. The health and sanitation index, with an average of 2.87, is deemed unfavorable; although some aspects, such as increased health information via social networks, are satisfactory, the use of online medical services is in a poor state, indicating a need for infrastructure and educational improvements in health.Furthermore, based on data analysis, the economic condition of smart villages in Hamadan County is also unfavorable in both agricultural and service sectors. The agriculture index, with an average of 2.82, indicates limited reliance on modern technologies in farming. The services index, at 2.43, shows a lack of extensive electronic services in administrative, insurance, trading, and transportation domains, as well as ineffective use of digital platforms and the internet to develop rural businesses.Finally, the status of institutional indicators—governance and planning—was examined, revealing fundamental weaknesses. Governance, especially in the context of employing electronic platforms to assess the performance of executive bodies, is in an undesirable condition. Planning, characterized by low participation and limited awareness, requires major reforms. Overall, the institutional indicators, with an average of 2.54, highlight an urgent need to improve policymaking processes and strengthen smart management institutions to achieve the development of smart villages. There is indeed a statistically significant difference at the 95% confidence level between the actual conditions for realizing a smart village and the theoretical average proposed by the research.The obtained averages indicate that the conditions of the smart village indicators in the studied area are not in a favorable state. Specifically, in the environmental dimension, the environmental, energy, and infrastructure indicators of the studied villages are all assessed as unfavorable. The environmental index has an average of 3.20, suggesting a relatively good status; however, the energy (2.75) and infrastructure (2.82) indicators, given the significance level and the negative upper and lower bounds, reveal poor conditions and substantial deficiencies in these areas. Overall, the environmental indicators' average of 2.92 emphasizes the unfavorable state and the need for continuous improvement in the environmental, energy, and infrastructure aspects of the studied villages.