Data Intelligence makes connected buildings smarter

IoT devices are formidable sources of data.

Imagine you are getting ready to go to work. Should you drive there or take public transport? The intelligent office building has the answers. It will tell you how many parking spaces are left based on occupancy data. And it will even provide you with traffic information for the nearest bus line. 

Now, imagine you are the owner of the same building and want to optimize its energy use. You can use the same car park occupancy dashboard to decide whether to open another level or close one and switch off the lights. Or schedule the closure every Wednesday when occupancy is always lowest.

By combining IoT and applying predictive algorithms, we can provide new services to users and operators - meaning more effective use of the possibilities offered by connected buildings.

Data Intelligence moves into the construction sector

The Building Operating System project is aimed at a new sector of activity for Akkodis’ Data Center, namely connected and intelligent buildings. It uses the same business approaches and technologies as the solution implemented for a bus manufacturer, which collects vehicle telematics data and enhances it with indicators, alerts and reports.

Julien Gréau, Delivery Manager for data projects, explains: "The challenge [of the Building Operating System] was twofold. On the one hand, we had to demonstrate our ability to understand the specific needs of the construction sector so that we can contribute our data expertise in the most effective way. Secondly, we aimed to build a partnership with our customer, a major player in the field, for other connected buildings projects in the future." 

Thanks to business workshops with the customer, Akkodis was able to capture the pertinent use cases. We aimed to collect various sources of data from the IoT equipment and applications, and to implement a software solution that transforms them into value-added information.

Step inside an intelligent building

Initially, Akkodis developed a proof of concept (POC) based on the client's head office buildings. 

The solution collects internal data (electricity consumption, building and car park occupancy) and those from external sources (weather conditions) and integrates them into their Datalab. This information can then be analyzed using decision-support tools and be displayed to all users. The indicators and alerts interface puts a formidable management tool in the hands of the people using the buildings. Is our office half-empty? Perhaps we could turn down the heating and turn off some lights. The restaurant's occupancy rate is only 28%? Seems like a good time for lunch.

Opening up new services for operators and users

In the future, the POC could be enhanced and include a predictive module for operators and a mobile application for users. The interface is fully scalable, allowing data access configuration according to user type. Intelligent building operators and administrators could determine energy requirements based on average consumption figures. The system would advise them on heating or cooling levels based on weather forecasts, to optimize energy costs. Employees would consult occupancy data to better organize their weeks, including meetings and telecommuting. The security services could have access to the tab displaying the intrusion detection system with video feeds. 

Taking its data science and data intelligence offering a step further, Akkodis proposed to couple the building management interface developed in Dash with a 3D digital twin. This would offer a system of alerts and troubleshooting for any piece of equipment in the building.

The predictive model is a strategic tool across industries

While the Building Operating System project was based on simulated data, it nonetheless demonstrated Akkodis' know-how and its ability to cater for any sector of activity. 

Akkodis is already working on the use case of a predictive power consumption solution for a car manufacturer who has to buy in advance the energy needed to run its factories. The predictive model is a strategic issue for this customer: based on the energy consumption summaries generated by its factories, the company will be able to predict its needs and negotiate the best rates with electricity and gas suppliers.

Thanks to Datakkod, the big data and data science platform, the Akkodis solution is able to collect data from production plans, meters and factories, right down to each machine on the vehicle production line. By fitting predictive algorithms for energy requirements and aggregating external climate data, Akkodis engineers will set up models for forecasting consumption and detecting anomalies. The control room will alert plant operators to any faults.

Today, the Data center can handle a wide range of subjects, including naval vessels, covering both data collection and data processing. "The associated projects are on a much bigger scale than what we have seen to date," concludes Julian. “This is a turning point for the growth of our center.”

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