My IoT Journey and Sustainable Development Goals
When I finished my bachelor’s, I was a bit lost in the vast world of engineering, with a multitude of interests but no clear direction. Discovering the Master’s in IoT was a turning point. It allowed me to blend my passion for electronics and programming while delving into diverse knowledge areas.
Last week, I was thrilled to receive an award for the best master’s thesis related to the Sustainable Development Goals (SDGs). My master’s thesis, “Design and Implementation Of A Procedure To Calibrate Photovoltaic Modules Based On A Sensor Network” aligns perfectly with multiple of the goals promoted by the United Nations.
These goals underscore the imperative use of clean energy sources, encourage innovation, advocate for environmental and economic sustainability, and support the sustainable development of cities and communities. You can explore these goals in greater detail at: https://sdgs.un.org/goals
Introducing My Master’s Thesis
In any engineering discipline, continuous optimization is a constant pursuit, and photovoltaic (PV) technology is no exception. To define the performance and behavior of PV modules, it is essential to measure their voltage and current, which are critical for assessing the module’s performance.
The characterization of PV arrays demands measurements under real operating conditions. Conventionally, this involves using a capacitive load, and the installation of resistance temperature detectors (RTDs) beneath solar panels to monitor temperature distribution across the modules. However, this approach required extensive wiring and the need for repeated measurements in various positions, leading to inefficiencies and potential inaccuracies
The new approach introduces the use of infrared sensor networks to automate the calibration procedure. Users will interact with the system through a dedicated mobile app that communicates with an edge device – a Raspberry Pi. This Raspberry Pi controls actuators and obtains data from sensors, which is then relayed to the mobile app and stored in the cloud to prevent data loss.
The project integrates a spectrum of different technologies. Electronic circuits, in particular capacitive load circuits. Thermal camera sensors are deployed for temperature data capture, while Analog-to-Digital Converters (ADCs) are connected through the I2C protocol for accurate voltage and current data acquisition. Communication is established via MQTT, enabling interaction between a Python application running on a Raspberry Pi (serving as the Edge device) and an Android Java mobile application. Furthermore, HTTP is employed for efficient file transfer to Cloud Storage, this way avoiding any possible data loss.
In summary, this represents a fully operational, scalable IoT solution for the efficient calibration of photovoltaic modules.
While the complete paper is not yet available in the “UPM Digital Archive,” I will update this post and share the link once it becomes accessible online.