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Secure Real-time environmental data and garbage counting system – promoting environmental awareness in an urban context


This use case, carried out in Fujisawa city in Japan, intends to address the main challenge of ensuring that the environmental data shared among stakeholders is done with trust. It aims to address the privacy protection and security assurance problems in existing mobile sensing platforms that are being used to collect environmental and garbage collection data in Fujisawa city, thus enabling secure data collection and sharing within and among hyper-connected smart cities.


The M-Sec Use case 3 is expected to improve the reliability and trust in the information from various sensors being used by garbage collection companies in Fujisawa city. These sensors are designed to provide benefit to the citizens and the municipal ward offices by providing timely and accurate information that these stakeholders can rely upon. More concretely, they provide real-time environmental data and garbage counting system to the population, thus promoting awareness in an urban context, as well as to the municipal officers, who can then take informed decisions about new garbage collection routes, for instance. With the M-Sec solution, multi-layers of security have been built-in in these sensors to ensure confidentiality, integrity, and availability of the data collected, to be used by stakeholders in a smart city.

The M-Sec Use Case 3 will be implemented in Fujisawa city, in Japan, as a pilot study until Q2-2021. This pilot study is expected to prove the power of multi-layered security mechanisms and privacy protection of the M-Sec platform for enabling trusted information sharing between the municipal ward offices and citizens, leveraging the mobile sensing platform that has been operated in the Fujisawa city for many years. The IoT devices (sensors), the cloud system (servers creating a sensor data exchange platform), and applications consuming sensor data streams included in the mobile sensing platform are now extended with multiple security mechanisms. The end-to-end security from IoT to cloud to end-user uses advance security concepts, techniques, and best practices for protecting data via advanced authentication mechanisms, encryption, monitoring, and security management tools. Security and privacy by-design and by-default has been incorporated to provide a trusted and reliable information system that can be replicated for similar platforms. Overall, it can be said that the M-Sec solution brings security and privacy added-value to existing sensors scattered across Fujisawa city.

Regarding main challenges facing the implementation of this Use Case, there was a concern of privacy leakage as the involved data include images of peoples’ faces and garbage trucks’ locations. The stakeholders like trucker drivers and the local government questioned if these data would be sent somewhere that was not sufficiently secure. Due to the M-Sec solution, the video data was going to be processed locally in the IoT device and deleted from the device so that only the generated information like amount of garbage would be sent to the servers. Therefore, no image data is sent outside the IoT device and citizens privacy is ensured.

Another challenge was the compliance with GDPR/PIPA data protection regulations when the video data coming from the sensors needs to be stored locally or sent outside. This challenge was addressed by the development of an on-site image processing component called “GANonimizer” that automatically removes privacy-related information from video data. In M-Sec’s implementation to this Use Case, the researchers the “GANonimizer” to automatically remove the images of passengers and private vehicles that appear in the video data.


This use case can be extended to other cities to protect mobile sensing systems established upon public/private vehicles like buses, taxies or cars that collect urban data including but not limited to traffic, environment and crowd.

If you want to know more about M-Sec’s Use Case 4 and how you can replicate it in your own city and/or region, you can directly contact Jin Nakasawa, at jin@ht.sfc.keio.ac.jp.