SENSOR COMPLEX AND HIERARCHICAL DATA PROCESSING ARCHITECTURE FOR SMART RETAIL ENTERPRISES

Abstract

The paper addresses the applied scientific problem of designing a sensor complex and a hierarchical data processing system for a smart retail enterprise as the basic component of an adaptive management information technology. It is shown that conventional centralised data acquisition and processing architectures fail to provide the required management responsiveness when a retail enterprise simultaneously generates data streams from radio-frequency identification devices, smart shelves, POS terminals, video analytics systems, microclimate and energy consumption sensors, as well as from corporate ERP, CRM and WMS information systems and digital sales channels. Twelve principles for constructing the sensor complex of a smart retail enterprise are formulated. They cover modularity, peripheral intelligent data processing, interface compatibility and standardisation, multi-source data integration, continuous monitoring, scalability, distributed processing, reliability and fault tolerance, energy efficiency, security and privacy, self-diagnostics and adaptability. Based on these principles, a structure of the sensor complex is developed that combines nine functional groups of data acquisition means together with edge computing nodes and IoT gateways. For the first time, an architecture of a five-level hierarchical data processing system is developed. It comprises the level of sensors and primary data sources, the level of local processing, the level of data integration and consolidation, the level of intelligent analysis and decision making, and the level of decision implementation, communication and monitoring. For each level the functions are defined and the corresponding data transformation operators are formalised, and their composition is presented as a generalised model describing a closed adaptive management loop in which the results of implementing managerial decisions form updated data for the next processing cycle. A mathematical model for evaluating the efficiency of the architecture is developed. It is based on a set of temporal, resource, informational and functional indicators: data processing time and managerial decision formation time, network traffic volume, utilisation of the computing resources of the central platform, the scalability indicator, availability and fault tolerance, the composite quality indicator of integrated data, and the adaptive management efficiency indicator. An integral efficiency criterion and a system of conditions are proposed, under the simultaneous fulfilment of which the developed hierarchical architecture outperforms the traditional centralised one. It is demonstrated that the proposed solutions reduce the time of data processing and managerial decision making, decrease the network load and the load on the central information and computing platform, and increase scalability, integrated data quality, system availability and the efficiency of adaptive management of a smart retail enterprise in real time.

Keywords: sensor complex, smart retail enterprise, hierarchical data processing system, edge computing, Internet of Things, data integration, adaptive management, architecture efficiency evaluation.