FreeDSM: An Open IoT Device for Citizen Light Pollution Monitoring

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Abstract

Light pollution has notoriously become the environmental problem that has grown the most in modern times, especially in highly populated areas and developed countries. It is a very serious worldwide issue, altering the natural day-night life cycle and, therefore, affecting the well-being of a large number of living species, including human beings. Indeed, some serious health diseases have been clearly linked to the incidence of light pollution. And, not to be forgotten, unnecessary outdoor lighting levels cause an enormous waste of energy linked to fossil fuel combustion and the aggravation of climate change. In this context, rising public awareness is key to addressing the true ecological, energetic, or medical dimensions of the problem; also, a technical global solution is demanded from and implemented by the implied administrations and stakeholders. It is in this context that light pollution levels should be massively measured at schools, homes, parks or hospital roofs, ideally by a low-cost, understandable and user-friendly device, and preferably controllable from our smartphones. Our proposal aims to cover this need by spreading and facilitating the use of FreeDSM, an open IoT device for citizen light pollution monitoring. FreeDSM is based on a Raspberry Pi Zero, a cheap and low consumption device, in which different components are integrated. The main component is the TSL2591, an optical light sensor that covers the wavelength range 300–1000 nm and a great dynamic range: 600,000,000:1. Other optional components can be incorporated to include ambient data, positioning and data connectivity. All the registered devices will be connected in a public access service, gathering the information by means of Fiware, an open framework for IoT environments.

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Silvelo, A., Dafonte, C., Boubeta, D., Ulla, A., Manteiga, M., & Masana, E. (2023). FreeDSM: An Open IoT Device for Citizen Light Pollution Monitoring. In Lecture Notes in Networks and Systems (Vol. 594 LNNS, pp. 634–641). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-21333-5_64

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