Energenius has designed and implemented a low-cost fog platform called GEM-Retail, composed of a cloud platform and edge nodes data gathering and run Artificial Intelligence (AI) models and advanced analytics. The fog nodes enable effective and responsive processing, filtering and elaboration of data related to energetic, environmental and business KPIs, offering an effective solution for real-time optimisation and actuation of relevant parameters of energy consumption, air quality monitoring and control of other business relevant metrics. The product was developed in collaboration with one of the leading companies in the EU in retail sales, with more than 2,000 stores worldwide. The objective of the GEM-Retail 2.0 project is to study, test and eventually adopt a series of big-data analysis tools, thanks to the resources offered by the EUH4D data services, to allow our product to grow in accordance with our envisaged commercial plan and effectively support two orders of magnitude more edge nodes than it currently does.
The analysis of energy consumptions, monitoring of environmental parameters and control of significant business indices play a fundamental role in the management of a network of retail stores. GEM-Retail 2.0 aim at designing and developing a plug-and-play, affordable and innovative product to effectively monitor, analyze and control thousands of shops.
The main innovation resulting from the GEM-Retail 2.0 experiment would be to integrate EUH4D’s big data services in a commercial tool, that would be extensively improved to handle much larger and more heterogeneous data sources, which in turn could allows us to make a qualitative steps in our embedded AI models for the efficient management of energy consumption and environmental quality metrics.
Very high heat with open doors during winter or lights on at noon in the summer, are just some of the wastes that happen to be witnessed by going to shops and malls. GEM-Retail 2.0 is a plug-and-play solution that allows to collect and process data related to energy and environmental KPIs, offering a new solution to reduce energy consumption, improve air quality and point out the most critical stores.
The GEM-Retail 2.0 project will aim at the following KERs:
a) Innovative data driven service: distributed, scalable, affordable product for retail energy and IEQ data management, integrating big-data and AI technologies
b) Business plan and model for the EU market
c) +30% global revenues by 2026
The project has five main KPIs:
- Increase the number of contemporary manageable shops from 100 to 10000
- Improve the accuracy prediction of AI algorithms in unknown climatic areas
- Collect additional field parameters related to customer well-being
- Integration of datasets from EHH4D catalogue and open repositories
- Contacts with additional potential customers in EU