It is shown that energy efficiency improvement of the region's economy is realized through the use of information-analytical means of supporting energy efficiency management, which are based on intellectual information, Web and telecommunication technologies. Architecture of an information-analytical system (IAS) for managing the energy efficiency of the region's economy has been developed based on the principles of modularity, openness, compatibility and use of a set of basic design solutions. IAS provides collection, processing and visualization of energy data, modeling, forecasting of energy efficiency management processes and support of energy efficiency management decisions for regional economic. The creation of a unified information space with reliable, complete and timely information that is used to generate effective management decisions is ensured. On the basis of the Internet of Things concept developed data collectors that are the spatially distributed small intelligent sensors linked to a cloud server. It is shown that it is expedient to develop the components of the geoinformation system for the IACEA region economy using Google Cloud Services and the specialized Google Maps API, which will provide promptly creation, modification and increase of information capabilities. It is argued that the additional involvement of programming tools, including JavaScript, using the Google Maps API provides the opportunity to develop a geoinformation system for the IAS for supporting energy efficiency management of regional economy, taking into account additional specific future requirements of the thesis system. It is proposed creation of the IAS for supporting energy efficiency management on the basis of databases and data warehouses, specialized publicly available GIS tools for visualization and analysis of energy consumption and energy efficiency data, which will ensure the feasibility and efficiency of generated management decisions. It is shown that the visualization of energy data and processing results in the most human-readable form with precise locations of the management facilities provides effective support for management decisions.
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