OpenTrack: a Sensor for Monitoring the Usage of Territory

Understanding how people and vehicles move through public spaces is essential for designing inclusive, safe, and efficient urban spaces. In the Mendrisio district (Switzerland), we deployed a low-cost, AI-powered sensor to monitor pedestrian and vehicle flows in different seasons. The sensor uses ca...

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Main Authors: D. Strigaro, A. Rollandi, M. Cannata
Format: Article
Language:English
Published: Copernicus Publications 2025-07-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/239/2025/isprs-archives-XLVIII-4-W13-2025-239-2025.pdf
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author D. Strigaro
A. Rollandi
M. Cannata
author_facet D. Strigaro
A. Rollandi
M. Cannata
author_sort D. Strigaro
collection DOAJ
description Understanding how people and vehicles move through public spaces is essential for designing inclusive, safe, and efficient urban spaces. In the Mendrisio district (Switzerland), we deployed a low-cost, AI-powered sensor to monitor pedestrian and vehicle flows in different seasons. The sensor uses camera-based image recognition to detect and classify objects in real time while preserving privacy by avoiding biometric or identity-related data capture, in full compliance with GDPR. The system was developed using open source hardware and software. Processes video frames on edge using a lightweight machine learning model optimized for embedded devices and periodically transmits summary data (object type, direction, timestamp) via NB-IoT to a centralized data platform. The collected data was used to generate temporal analyses and heatmaps of space usage and to validate the classification accuracy in different weather and lighting conditions. Field tests demonstrated the sensor’s capability to operate autonomously for extended periods with low power consumption, while highlighting limitations in NB-IoT connectivity in specific locations. Despite these constraints, the system provided valuable information on public space utilization, identifying peak hours and spatial patterns relevant for mobility planning and urban design. This approach offers a replicable and cost-effective solution for municipalities seeking data-driven support for decision-making. By combining privacy-sensitive AI, open technologies, and standard data models (such as SensorThings API), the project contributes to a more transparent and inclusive digital urban ecosystem.
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spelling doaj-art-a09be9e071fd4c0a889664458da93ff92025-08-20T03:28:29ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342025-07-01XLVIII-4-W13-202523924410.5194/isprs-archives-XLVIII-4-W13-2025-239-2025OpenTrack: a Sensor for Monitoring the Usage of TerritoryD. Strigaro0A. Rollandi1M. Cannata2Institute of Earth Sciences, DACD, University of Applied Sciences of Southern Switzerland (SUPSI), Via Flora Ruchat-Roncati 15, CH-6850 Mendrisio, SwitzerlandInstitute of Earth Sciences, DACD, University of Applied Sciences of Southern Switzerland (SUPSI), Via Flora Ruchat-Roncati 15, CH-6850 Mendrisio, SwitzerlandInstitute of Earth Sciences, DACD, University of Applied Sciences of Southern Switzerland (SUPSI), Via Flora Ruchat-Roncati 15, CH-6850 Mendrisio, SwitzerlandUnderstanding how people and vehicles move through public spaces is essential for designing inclusive, safe, and efficient urban spaces. In the Mendrisio district (Switzerland), we deployed a low-cost, AI-powered sensor to monitor pedestrian and vehicle flows in different seasons. The sensor uses camera-based image recognition to detect and classify objects in real time while preserving privacy by avoiding biometric or identity-related data capture, in full compliance with GDPR. The system was developed using open source hardware and software. Processes video frames on edge using a lightweight machine learning model optimized for embedded devices and periodically transmits summary data (object type, direction, timestamp) via NB-IoT to a centralized data platform. The collected data was used to generate temporal analyses and heatmaps of space usage and to validate the classification accuracy in different weather and lighting conditions. Field tests demonstrated the sensor’s capability to operate autonomously for extended periods with low power consumption, while highlighting limitations in NB-IoT connectivity in specific locations. Despite these constraints, the system provided valuable information on public space utilization, identifying peak hours and spatial patterns relevant for mobility planning and urban design. This approach offers a replicable and cost-effective solution for municipalities seeking data-driven support for decision-making. By combining privacy-sensitive AI, open technologies, and standard data models (such as SensorThings API), the project contributes to a more transparent and inclusive digital urban ecosystem.https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/239/2025/isprs-archives-XLVIII-4-W13-2025-239-2025.pdf
spellingShingle D. Strigaro
A. Rollandi
M. Cannata
OpenTrack: a Sensor for Monitoring the Usage of Territory
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title OpenTrack: a Sensor for Monitoring the Usage of Territory
title_full OpenTrack: a Sensor for Monitoring the Usage of Territory
title_fullStr OpenTrack: a Sensor for Monitoring the Usage of Territory
title_full_unstemmed OpenTrack: a Sensor for Monitoring the Usage of Territory
title_short OpenTrack: a Sensor for Monitoring the Usage of Territory
title_sort opentrack a sensor for monitoring the usage of territory
url https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/239/2025/isprs-archives-XLVIII-4-W13-2025-239-2025.pdf
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