E!114129 MEWS - A distributed, scalable and cost-effective Mass movement Early Warning System

We want to develop a scalable Mass movement Early Warning System (MEWS) for early detection of landslides, rockfalls and avalanches. It will collect large amounts of data from an array of field-deployed, wireless, low cost and self-powered IoT Devices, hosting many sensor types. The data will feed a cloud based system and use machine learning for fast processing and decision making. We will deliver a prototype of such a system to demonstrate its potential in the case of avalanche detection. We want to do this because mass movements, like landslides or avalanches, pose dramatic risks to individuals, populated areas, and critical transportation infrastructure. IoT technology provides the opportunity to develop an early warning system predicting the probability of an event with sufficient accuracy to help mitigate the consequences. Reducing risk reduces cost - both in terms of societal exposure, but also in material damages. The Norwegian partners in this Eurostars project, are: 1) Spordata AS, a Norwegian SME that focuses on development of IoT technology and selling resulting products and services to the market. 2) NGI (Norwegian Geotechnical Institute) is Norway's leading geotechnical professional environment and an international center for research and consulting in engineering-related geosciences. In the first reporting period (Q3/Q4-2020), Sportdata and NGI have collaborated in the consortium on defining the overall conceptual design of the system, and on establishing theme groups in the various subject areas and appointing leaders for these. Spordata has participated in two such thematic group meetings. In addition, Spordata has started the in-house development of the first version of the multisensor IoT unit as well as the in-house development of the LoRa gateway to be used in this project. NGI has started collecting and structuring historical data from the test location Ryggfonn / Fonnbu, and has carried out an internal assessment of relevant parameters / sensors for landslide warning systems, including field inspections at the installation. In this reporting period, 2021, Spordata has developed 2 versions of the multisensor IoT device. 8 units were produced by the first version and were successful, but were completed so close that the second version, which is to be used in NGI's experimental field (Ryggfonn) in the upcoming winter, that mass data from this first version was not used by the consortium. Development of version 2 of the multisensor IoT unit, which was this year's main goal, has also been successfully completed and 15 units of these have been produced. Poles and fastening mechanics for these 15 for placement in the experimental field were also developed and produced. In collaboration with NGI, Spordata deployed these 15 complete multisensor IoT units in the Ryggfonn experimental field in September. An adapted first version LoRa Gateway was also internally developed during the period, which was also deployed in the experimental field for receiving and transmitting all the data generated by the 15 multisensor IoT devices. The system works and is expected to generate data continuously through the coming winter. In this reporting period, 2022 and the last one, the 15 multisensor IoT devices was taken down again from NGI's experimental field (Ryggfonn) after the winter season - after they had delivered quite good data throughout the entire winter. Thus, the long life-time on small batteries and in sub-zero temperatures was proven successfully. During the summer Spordata upgraded the 15 multisensor IoT devices with some bug-fixes and new features. This fall the 15 units was once more installed back at Ryggfonn, by NGI and Spordata, and they are currently successfully and continuously delivering delivering data. NGI and the two international partners continue to work on the data analysis and the AI methods for snow-avalanche early-warning, also after this project officially now has ended in Norway.

This project has been well aligned with the strategy for the technology road map and the business areas that Spordata is targeting. Carrying the project trough has without doubt improved very relevant competence for the company’s R&D employees. The project have had two international (non-Norwegian) partners, Beia in Romania and Amplia in Spain, and up to this project started, Spordata had all its activities going in Norway only. It’s been a positive experience for the company to be part of this international consortium, and the ambition of the consortium is to jointly seek business opportunities on the international arena based on the concepts and the results of the project. This opportunity is very valuable to Spordata, and totally new. In terms of possibility for revenue increase the original plan involves following up with commercialization of the overall outcome of the project, in joint efforts between Spordata, Beia and Amplia. Furthermore this plan involves the creating of a start-up organization that further will develop both markets and technology. Growth of the spin-off will be based on financial and technical contributions of additional owners/partners joining this organization. There has been no discussion during the project to change this plan. However, this report is following Spordata's completion of its part of the project, whereas the two other partners have not yet completed their work (on intelligent interpretation of the data). This means that at this stage (Jan. 2023), we don't yet know the result of the "early-warning" efficiency and usefulness of the system developed, so it is still uncertain how such joint international commercial investment will play out. From Spordata's point of view, however, we know that the developed IoT Devices and the LoRa solution surrounding these, can play an important role in new business areas here in Norway. One such area is the monitoring of water-level and currents that is needed in hydroelectric production, and are already looking into such opportunities. Spordata has the possibility to pursue such opportunities on our own, since this can be done without "intelligent interpretation of the data" - which is the R&D area of the two other commercial partners in the Eurostars project. For NGI, this project has indeed increased their knowledge of the possibilities that IoT technology for their needs will provide, and have been demonstratet how they can further use this to solve their problems in the relevant field of application.

We want to develop a scalable Mass movement Early Warning System (MEWS) for early detection of landslides, rockfalls and avalanches. It will collect large amounts of data from an array of field-deployed, wireless, low cost and self-powered IoT Devices, hosting many sensor types. The data will feed a cloud based system and use machine learning for fast processing and decision making. We will deliver a prototype of such a system to demonstrate its potential in the case of avalanche detection. We want to do this because mass movements, like landslides or avalanches, pose dramatic risks to individuals, populated areas, and critical transportation infrastructure. IoT technology provides the opportunity to develop an early warning system predicting the probability of an event with sufficient accuracy to help mitigate the consequences. Reducing risk reduces cost - both in terms of societal exposure, but also in material damages. The Norwegian partners in this Eurostars project, for whom this application-form is for, are: 1) Spordata AS, a Norwegian SME that focuses on development of IoT technology and selling resulting products and services to the market. 2) NGI (Norwegian Geotechnical Institute) is Norway's leading geotechnical professional environment and an international center for research and consulting in engineering-related geosciences. Spordata and NGI will have overall responsibility only for parts of the developments in the overall projects and consequently also only for parts of the primary and secondary objectives (in previous section).