# Cost-Effective Temperature Sensor for Monitoring the Setting Time of Concrete
## 2 Materials and Methods
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Composition (\%)** & **CEM I** & **CEM II** & **Standard Fine** & **Fine** & **Coarse** & **Recycled Concrete** & **Zeolite** \\  & **(\%)** & **CEM II** & **Aggregate** & **Aggregate** & **Aggregate** & **Aggregate** & **Zeolite** \\ \hline Al\({}_{2}\)O\({}_{3}\) & 4.76 & 5.09 & 1.55 & 0.73 & 1.23 & 4.25 & 9.64 \\ \hline BaO & 0.08 & 0.09 & 0.02 & 0.02 & 0.01 & 0.04 & \textless{}0.01 \\ \hline CaO & \textless{}60.00 & \textgreater{}60 & 0.16 & 18.50 & 21.20 & 10.85 & 1.20 \\ \hline Cr\({}_{2}\)O\({}_{3}\) & 0.01 & 0.01 & \textless{}0.01 & \textless{}0.01 & \textless{}0.01 & 0.14 & \textless{}0.01 \\ \hline Fe\({}_{2}\)O\({}_{3}\) & 3.57 & 2.7 & 0.61 & 0.25 & 0.48 & 1.94 & 1.27 \\ \hline K\({}_{2}\)O & 1.04 & 0.96 & 0.61 & 0.36 & 0.31 & 1.46 & 2.14 \\ \hline MgO & 1.47 & 1.8 & 0.09 & 0.16 & 0.55 & 0.45 & 1.09 \\ \hline MnO & 0.05 & 0.07 & 0.01 & 0.01 & 0.01 & 0.02 & \textless{}0.01 \\ \hline Na\({}_{2}\)O & 0.30 & 0.14 & 0.19 & \textless{}0.01 & 0.02 & 0.54 & 3.63 \\ \hline P\({}_{2}\)O\({}_{5}\) & 0.12 & 0.16 & 0.03 & 0.01 & 0.03 & 0.05 & \textless{}0.01 \\ \hline SO\({}_{3}\) & 3.24 & 2.95 & 0.02 & 0.06 & 0.05 & 0.32 & \textless{}0.01 \\ \hline SiO\({}_{2}\) & 19.86 & 19.84 & 95.44 & 64.34 & 59.17 & 72.25 & 68.42 \\ \hline SrO & 0.03 & 0.11 & \textless{}0.01 & 0.01 & 0.01 & 0.02 & \textless{}0.01 \\ \hline TiO\({}_{2}\) & 0.25 & 0.24 & 0.06 & 0.04 & 0.14 & 0.16 & 0.11 \\ \hline LOI & 3.77 & 6.45 & 0.47 & 14.84 & 17.49 & 7.91 & 11.58 \\ \hline \end{tabular}
\end{table} 
Table 3: Composition of materials by XRF. In addition, a BME280 (Adafruit, from New York, NY, USA) environmental sensor was used to verify that the conditions were suitable for curing the samples. The communication protocol makes it possible to control several sensors distributed over a wide area with a single microprocessor. Data transmission was carried out via Wi-Fi connection. The data was transmitted by Wi-Fi connection to our IoT platform, known as Tellus IoT (V 2.1), which allows storage to take place in the cloud as well as real-time visualization of the data generated by the project (Figure 2). This IoT infrastructure enables the effective management of real-time data to optimize processes, making it the digital core for informed and up-to-date decision-making [36]. Figure 1: Particle size distribution. (**a**) comparison of the particle size distribution of the standard fine aggregate and the fine aggregate used. (**b**) comparison of particle size distribution of natural coarse aggregate and recycled concrete aggregate. Two separate tests were carried out in order to be able to adjust the parameters as necessary. In the first trial, two Node MCU Lolin v3 microcontrollers and a power supply were set up. The environmental microcontroller was physically connected via a cable to the BME280 sensor inside the wet chamber. The other microcontroller was connected to the different DS18B20 sensors via the electrical terminals. The seven sensors inside the wet chamber measured the temperature of the specimen mixture during the setting time and the temperature of the water. The connection diagram and the final schematic of the first prototype are shown in Figures 3 and 4. In the second test, a power supply was established for a Lolin v3 Node MCU microcontroller. To this end, the previous design was optimized by making small necessary modifications, as shown in Figure 5.  
The integration of the sensors, together with the intercommunication and real-time data analysis capability provided by the Tellus UPM Ecosystem, allow us to obtain a solution that can adapt and respond to the specific needs of the industry, leading the way towards sustainable and technologically advanced innovations. Figure 3: Schematic of DS18B20 sensor connection. Figure 2: Conceptual diagram of communication system and IoT platform operation.