Abstract:

This contribution presents the main results of monitoring green urban areas with IoT technology of the Erasmus+ project SUTEE – Showcasing Urban Trees for Environmental Education with IoT Technology (2023-1-ES01-KA220-SCH-000153498). The objective was to design, implement, and validate an accessible technological ecosystem enabling students and teachers to monitor key environmental parameters in urban contexts, fostering data literacy and environmental awareness through authentic inquiry-based learning.

The team developed a complete IoT toolkit combining low-cost, low-power, and portable devices suitable for school excursions in different parts of the city. The toolkit integrates multiple environmental sensors for CO₂, temperature, humidity, particulate matter (PM1.0/PM2.5), volatile compounds, soil moisture, and surface temperature, connected to a Raspberry Pi Zero acting as a compact and affordable processing unit. This configuration ensures sufficient autonomy for field activities of up to two hours and makes the system economically viable for schools and teachers. Complementary commercial devices were also tested to compare measurement performance and reliability.

To support data collection and contextualization, the produce produced two Android mobile applications. The first app collects sensor data, visualizes the readings in real time, enriches them with GPS location, and automatically uploads them to a cloud platform for later analysis. A second app measures environmental noise, translating decibel levels into an intuitive colour-coded risk scale (e.g., normal sounds, busy road, airplane/concert), enabling students to compare acoustic conditions across urban settings. These tools empower learners to investigate how parks, pedestrian areas, roads, or tree-covered zones influence environmental quality.

A central result of project is the integration of citizen-generated data into a visualisation platform that displays excursion routes on interactive maps and provides time-series charts for each environmental variable. A second server offers detailed drill-down views of each measurement point, enriching the exploratory potential for classroom discussions. Furthermore, an AI-based explanatory tool was developed to help young students interpret differences in humidity and temperature between contrasting urban locations through accessible, emoji-supported explanations.

The work package also laid the foundations for learning activities by deploying the open educational resource platform ViSH, enabling the creation, publication, and reuse of interactive presentations, SCORM packages, virtual tours, and multimedia activities. This infrastructure ensures the pedagogical integration of IoT-based findings and supports teachers in designing structured learning scenarios.

In sum, the project demonstrates how affordable IoT sensing, mobile data collection, and accessible visualisation tools can empower learners to understand urban environmental phenomena through hands-on inquiry, supporting both green competences and digital data skills in line with EU educational priorities.

Keywords:

Internet of Things (IoT), Urban Environmental Monitoring, Environmental Education, Citizen Science, Data Literacy.