INTELLECTUAL MODELS FOR THE DEVELOPMENT OF SECURITY SYSTEMS AND ENERGY AUTONOMY IN RURAL COMMUNITIES
DOI:
https://doi.org/10.32718/agroengineering2025.29.185-197Keywords:
rural communities, development, projects, security, energy, optimization, intelligent models.Abstract
An analysis of existing approaches to spatial planning of security systems and energy autonomy of rural communities has been carried out. It has been established that traditional methods of deploying rescue teams and planning energy consumption are mostly based on average indicators and do not take into account various scenarios or the complex impact of multiple risk factors. The feasibility of using intelligent models, in particular p-center, p-median, recurrent neural networks (LSTM), and hybrid algorithms, has been substantiated. These models allow minimizing response time to emergencies, balancing the energy load of facilities, and predicting the level of community autonomy. The Python program developed provides spatial modeling of the availability of volunteer rescue teams using OpenStreetMap geospatial data and optimization methods. According to the results of modeling in Sheptytskyi urban community of Lviv region, it was established that the maximum response time to emergencies was reduced from 27 to 15 minutes, the average response time from 18 to 12 minutes, the proportion of the population covered within a 15-minute drive of rescuers increased from 54% to 82%, and the protection of critical infrastructure facilities increased from 61% to 89%. This confirms the effectiveness of the p-center model for territories with scattered settlements and demonstrates the practical significance of the proposed approach for community security and development strategies. Further research should focus on integrating energy balance forecasting models with algorithms for selecting locations for renewable energy sources, which will create a unified toolkit in the form of a decision support system for community project managers.
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