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Using data for good: Digitalized water for smart cities

Sustainable Development Goals

Through the years, our Technology for Good blog has highlighted a number of smart sustainable initiatives which Ericsson is involved in to monitor environmental and climate changes, provide safer drinking water and help build smarter cities. Some of these projects in particular, such as microwave-based rain monitoring, are examples of how we can use data to increase our knowledge of environmental change and potentially mitigate pollution and climate change.

Digitalized water for smart cities

I recently wrote about this initiative for the ITU Journal, which you can read today. The article starts with a description of the project mentioned above, how data can be used for good and concludes by identifying which obstacles still stand in the way of cities and other decision-makers being fully able to utilize data for the good of the environment.

Read the Digitalized Water for Smart Cities article on the ITU Journal website today.

Water-quality- and rain monitoring projects

Ericsson’s ongoing water-quality monitoring project in Stockholm has now entered its second and final phase, before its scheduled conclusion in 2020. The project, a joint demonstrator project with the City of Stockholm, local and national academia and telecom operator Telia, is scoped to develop algorithms for automatic detection of changes in the water quality.

The rain monitoring project, which utilizes microwave backhaul in commercial telecom networks to detect rainfall in real time, is now live with trials taking place across Sweden, Germany and Rwanda. The scope of the project is to fine tune the rain detection algorithms, industrialization and development of business models.

Additionally, the trial in Rwanda which is financed together with DIFID, is investigating sustainable business models and use cases which have a real impact in fighting poverty, disease and climate change.

Smart city challenges

In the ITU article, I identify the different challenges related to implementation of data-driven solutions. There are several aspects that need to be considered, such as sensor and integration costs, but also organizational and process limitations. A smart city, for example, would require several departments to streamline their processes in order to be able to fully take advantage of the data that is generated through sensor based systems.

Short on bedtime reading? Read the Digitalized Water for Smart Cities article for free today!


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