# A Portable Non-Motorized Smart IoT Weather Station Platform for Urban Thermal Comfort Studies
## 4 Efficiency and Performance of the Proposed Weather Station Platform  
This section discusses the five tests to assess the proposed platform's performance. Mobile weather stations are used under two scenarios: 'On the move' and 'Stop-and-go' (i.e., the station was stopped at the intended locations for the measurements [8]). Therefore, we considered the same scenarios in our tests while mounting the edge device on a bike, as shown in Figure 3.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Weather Variables (Unit)** & **MAE** & **RMSE** \\ \hline Air Temperature (\({}^{\circ}\)C) & 0.10 & 0.33 \\ \hline Relative Humidity (\%) & 1.72 & 2.34 \\ \hline Wind speed (km/h)—hourly average & 0.21 & 0.25 \\ \hline Wind speed (km/h)—10 min average & 0.11 & 0.25 \\ \hline \hline \end{tabular}
\end{table}
Table 2: MAE and RMSE values of the edge device against the Davis weather station.  
Figure 3: The edge device is mounted on a bike for non-motorized mobile weather measurements.  
The developed device depends on the cellular network to send the readings to the server. Therefore, two routes, A and B, were selected for the 'on the move' scenario (Figure 4). Route A presents an open area containing few or no buildings, while Route B presents a densely built city centre. For the'stop-and-go' scenario, a few locations were chosen in a residential neighborhood where low-rise buildings are sparsely placed, and a few locations were chosen in a commercial neighborhood that is densely built with mid/high-rise buildings (see Figure 5). The chosen locations represent various street orientations and widths, surrounded by buildings and trees.  
'On the move' scenario: Route A--Started from the residential neighborhood (Dalmarnock in Glasgow), moved to the neighboring streets with a warehouse (similar building density to Dalmarnock), and travelled along the River Clyde to Glasgow Green Park. The route continues through the park, with no buildings around, and entered Glasgow city centre via the riverside in the city centre. The collected data along this route were divided into five parts for a detailed analysis of the results, and these five parts are tabulated in Table 3.  
Figure 4: ‘On the move’ scenario: Route A (**Left** image) and Route B (**Right** image).  
Figure 5: ‘Stop-and-go’ scenario: Residential neighborhood test locations (**Left** image) and Commercial neighborhood test location (**Right** image).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Route A—Parts** & **Description** \\ \hline Part 1 & Residential and Warehouse \\ \hline Part 2 & Riverside with greens \\ \hline Part 3 & Glasgow Green Park \\ \hline Part 4 & Riverside adjacent to the city centre \\ \hline Part 5 & Glasgow City Centre \\ \hline \hline \end{tabular}
\end{table}
Table 3: Five geographical ‘On the move’ scenario Route A parts.  
'On the move' scenario: Route B--Started from Glasgow Caledonian University (GCU), covers part of West Nile Street, moves on to Bath Street, reaches the M8 highway, takes the cycle and pedestrian pathway, and travels on Waterloo Street and Hope Street to return to the starting point.  
'Stop-and-go' scenario: Residential and Commercial neighborhoods--Data at each fixed location, marked in Figure 5, were collected for about 10 min within 13:00 to 17:00 UTC hours. The device was not turned off until data collection was completed at all locations. The switch with the green Light-Emitting Diode (LED) in the device was used to tag the data collected at each specific location. Overall, the data was collected over two days: Day 1 for residential areas and Day 2 for commercial areas.