Reducing Environmental Impact Through Technology?

In a society where the digital is ubiquitous, how can cities make it an asset in their environmental impact? How can I invest in valuable projects? Giving the environment a central place can make sense of a digital strategy and contribute to improving quality of life and reducing costs for businesses and communities alike.

Optimizing waste collection, increasing the efficiency of sorting, energy performance of sewage treatment plants, preserving water resources… Many communities are now relying on data technology to create cities that are less energy-intensive, cleaner and closer to citizens.

Technology for the environment

Since the Grenelle 2 act, communities with more than 50,000 inhabitants and public institutions with more than 250 people have an obligation to measure their impact on the climate, via a greenhouse gas balance. Communities responsible for implementing a territorial air energy climate plan (CECP) must also carry out a preliminary assessment of greenhouse gas emissions. These exercises must be carried out at the territory and skill level. In other words, these reviews relate to the emissions generated by the operation of the community’s activities and services, and by the implementation of their skills. Most communities choose to stick to the strict obligation: to calculate the footprint of direct emissions (energy consumed directly for heating and transportation) and indirect emissions related to electricity consumption or heat. Consideration of other indirect emissions is optional but recommended by regulation. In fact, very few choose to expand their assessment to this scope.

While it would take 1.7 planets today to meet the needs of humanity without jeopardizing those of future generations, preserving resources and making progress in the circular economy is a major challenge. To do this, increasing recycling performance and ensuring an outlet for recycled raw materials is a major challenge. New technologies applied to waste collection are an opportunity to find new answers to the associated environmental challenges, from reducing vehicle consumption to reducing olfactory and visual nuisance. It is with this in mind, for example, that Veolia mobilizes its hypervision technologies. By collecting and collecting data from the field, from connected objects, and by combining the potential of digital with human expertise, it is possible to produce new analyses to improve operations in the field.

Reducing the negative environmental impact of buildings

More and more businesses and communities are now working to reduce their environmental impact and, at the same time, make financial gains. This is the case for example of Rueil Malmaison, Gennevilliers, Clamart or the Rouen Metropolis who were able to optimize their infrastructure to obtain energy gains of more than 15%. To do this, they were able to count on the solution of Kipsum, a start-up for energy optimization of buildings that responds to the major challenges of today’s society: reducing the environmental footprint and digitalizing it. Created in 2018, the start-up designs and installs a set of sensors for its customers that allow them to reproduce and generate a multiphysical model of the building, its heating system and its occupants, after sending data to the recommendations for optimization. The start-up made in France now collaborates with many private customers such as Renault and has recently been honored at CES in Las Vegas.

“We use the cloud to track all the measurements we take in the buildings we optimize. Security and confidentiality are key elements for us and our customers. The benefit is not having to manage network infrastructure and be easily adaptable in storage capacity or download speed depending on the needs and the number of customers,” explains Philippe Chevalier, CEO and co-founder of Mr. Kipsum. Heating, heat diffusion and distribution processes, intrinsic building quality and occupant habits, … How can the negative environmental impact of buildings be reduced? A solution based on artificial intelligence that takes these four elements into account, in order to enable managers to achieve their energy optimization goals.

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