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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - PREDISMART (AN INTELLIGENT PREDICTION SYSTEM FOR THE SMART EFFICIENT USE OF RESOURCES IN CITIES)

Teaser

Summary

PrediSmart supports the needs of society to reduce energy, water, waste, operation & maintenance costs for a more environmentally friendly and efficient use of resources. Big Data Analytics and Cloud Computing technologies are widely used today by many companies in the commerce sector to analyse customer behaviour, forecasts sales and to guide business strategies.
PrediSmart is aligned with the H2020 objectives for energy and CO2 emissions reduction by saving energy and resources. Its implementation supports the Energy Efficiency Directive, and the Energy Performance of Buildings Directive.
PrediSmart is the result of Datapoleâ€™s technology on statistical data analysis, simulation and prediction for energy, operational and resource efficiency. It is an innovative software system that integrates four Expert Modules for an efficient management of energy, services (including building maintenance and facility management), water and waste.
We now aim at enhancing the product functionalities of PrediSmart, making it a complete off the shelf Big Data Analytics solution for energy, operational and resource savings unique in the European market. Our goal is to launch PrediSmart to the European markets expanding our customer base across countries in Europe. We will implement our new set up software modules and integrate them to our existing expert modules into an off the shelf complete software platform.

Work performed

Since the beginning of the project, we developed connectors for BAS, CMMS, IoT and Waste data suppliers, which will allow an automated collection of data for all format we developed for. This work heavily relied on a strong data analysis preparatory work done by our data team.
We also reoriented our server management, migrating our platforms to a new host (AWS) which will give us more flexibility, efficiency and cost control for the future of our project. This migration is completed, we are developing a new interface and an automated setup. A demonstrator is currently being developed, with the automated data model generation being achieved, and will allow the interested pilots/clients to create an account, send a formatted data and try our solution with minimum efforts.
Our commercial team attended 13 events related to smart city and facility management which led to more than 200 contacts taken with various societies of which 160 we still have relations with.

Final results

Though making significant progress, the project is still currently in the preparatory phase. Pilots should be coming soon, which will allow us to take PrediSmart to the next level with field tests and have a clearer vision of the results of our activity. Nevertheless, we have most reasons to believe that our first expectations about socio-economic impact are realistic. We aim at an improvement of 10% for energy efficiency and 30% for resource efficiency.
We expect to be able to provide this improvement to major actors in energy, transport and building industries (among others), which should represent a positive impact.