EnergismeSmart city, a territorial model based on the control of data

Smart city, a territorial model based on the control of data

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How to become a smart city?
The city of the future will have to meet new challenges, particularly in terms of the environment.
The smart city model is based on the digital transition as a lever for transforming territories. In this model, data plays a key role in the service of collective intelligence and general interest.
By strengthening their data management, Energisme supports the transformation of local authorities into smart territories.

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What is the smart city?

The smart city is an urban development concept that aims to reconcile the challenges of ecological transition and quality of life for residents, thanks to the growing integration of digital technologies.

The smart city has the same objectives as the sustainable city:

  • Energy transition
  • Comfort of the inhabitants
  • Optimization of collective resources

To achieve these goals, the city of tomorrow relies on a combination of :

  • Collective intelligence, through the active participation of citizens and stakeholders in local decision-making.
  • Artificial intelligence: in the smart city model, data plays a central role in informing decisions.

N’Gage solution

The N’Gage solution, developed by Energisme, enables local authorities to improve their data management and use it for the general interest. To do so, it is based on 2 complementary axes:

Smart metering : solution de mesure des communications

The intensification of data collection via smart metering
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Éclairage public intelligent | Smart Lighting | Energisme

The intensification of data collection via smart lighting
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Traitement des données énergétiques & Smart Cities

Data processing and analysis using the platform's artificial intelligence modules
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How does a smart city work?

Energy data collection
Smart city -  collect data - Energisme

Energy data collection

The smart city meets a sustainability objective

Energy efficiency is at the heart of the concept. To achieve this goal, the smart city relies on an energy management system through the collection and analysis of energy data.

Indeed, to optimize public lighting or utility infrastructures, for example, local authorities must first collect data.

This data relates to the uses of the inhabitants. For example, data on the number of people passing through or visiting a sector of the city provides a better understanding of urban lighting needs.

Local authorities also organize the collection of energy data on their infrastructures (public service buildings, public lighting, etc.). These energy data come from :

  • Energy supply bills and contracts
  • Remote reading from energy network managers
  • Connected objects equipped with intelligent sensors
Data processing and analysis

Data processing and analysis

Data quality is a key success factor in energy management

The development and widespread use of information technology makes it easier to collect energy data. 

Thanks to IoT sensors, data generation is no longer exclusively the responsibility of third parties. Local authorities are gaining autonomy over data production. In the era of Big Data, the challenge is no longer to collect data but to efficiently process large volumes of data from multiple sources.

The N’Gage platform developed by Energisme responds to the energy issues of the smart city. It allows local authorities to :

  • collect at source, clean and aggregate energy data automatically
  • perform a complete data analysis by cross-referencing energy data with other variables using artificial intelligence
  • Generate reports that are easily understandable and usable by stakeholders
  • Directly control the smart city from the platform thanks to these analyses and their lessons learned (remote control of equipment, turning off/on street lights, etc.)
Data-driven strategic decisions
décisions stratégiques - smart city - Energisme

Data-driven strategic decisions

The purpose of using energy data is to feed into decision-making at the local level

In the smart city model, artificial intelligence feeds collective intelligence. This mode of operation presupposes a collaborative and virtuous use of data, which manifests itself through :

  • clear information on the use of personal data
  • citizens’ consent to the collection of their data 
  • Accessibility of data to all stakeholders (policy makers, project leaders, citizens,…)

The opening of public data is at the heart of the smart city concept. Managing energy data is a public service mission. It is therefore up to local authorities to promote data sharing and its development. 

This open data operation creates the conditions for collaborative energy management. Data is made available through a public database that is easily accessible to all partners concerned by energy and digital transition issues.

Finally, the smart city encourages the development of smart grids, with a dynamic of increased collaboration, particularly between the energy consuming community and the network managers. In concrete terms, a smart grid enables :

  • Predict, thanks to data, the state of the networks and act or react accordingly
  • adjust energy flows according to demand and usage

The implications are multiple: optimization of public lighting, better energy management of public buildings…

What are the most successful Smart City models?

The smart city model is relatively recent and the cities of tomorrow are still largely unbuilt. Nevertheless, some communities are already emerging.


Singapore is regularly cited as an example. The city-state has launched a global “smart nation” program. The local government has invested heavily in equipping the city and its urban furniture with intelligent sensors to analyze urban behavior. 

Singapore’s smart city has many uses: 

  • traffic fluidity and development of green mobility
  • energy management
  • improvement of the comfort of the inhabitants and answers to the ageing of the population

In Europe, the city of Copenhagen has set up a comprehensive system for monitoring energy consumption, air quality, waste management and traffic in order to meet environmental challenges.

The objective is twofold:

  • facilitate traffic flow in real time
  • optimize energy consumption

In these two examples, the ability to manage massive data translates into the creation of new innovative services.

How to become a smart city?

The evolution towards the smart city requires rigorous data management. The challenge is not only technical but also political.

Of course, the quality of the data is essential, but so is the governance of the data. 

To become a smart city, a territory must therefore go through 4 stages.

The platform developed by Energisme supports smart cities in their data management challenges.

Our expertise in the data path, from collection to exploitation, positions us as a trusted partner for territories wishing to build the cities of tomorrow today.

Define a political and collective vision of the city of tomorrow: set the major objectives to be achieved in partnership with local stakeholders
Set up a global data collection system (notably via IoT sensors) with the support of citizens
Adopt a data processing and analysis solution to enhance the value of the data and make it accessible and usable
Use data for the general interest, especially in decision-making on energy efficiency of public infrastructure