Electricity consumption is rising due to population growth, climate change, urbanization, and the increasing use of electronic devices. The trend of the Internet of Things has contributed to the creation of devices that promote the thrift and efficient use of electrical energy. Currently, most projects relating to this issue focus solely on monitoring energy consumption without providing relevant parameters or switching on/off electronic devices. Therefore, this paper presents in detail the design, construction, and validation of a smart meter with load control aimed at being part of a home energy management system. With its own electronic design, the proposal differs from others in many aspects. For example, it was developed using a simple IoT architecture with in-built WiFi technology to enable direct connection to the internet, while at the same time being big enough to be part of standardized electrical enclosures. Unlike other smart meters with load control, this one not only provides the amount of energy consumption, but rms current and voltage, active, reactive, and apparent power, reactive energy, and power factor—parameters that could be useful for future studies. In addition, this work presents evidence based on experimentation that the prototype in all its readings achieves an absolute percentage error of less than 1%. A real-life application of the device was also demonstrated in this document by measuring different appliances and switching them on/off manually and automatically using a web-deployed application.

The present investigation analyzes the performance of a Hatz diesel engine that has 912 cubic centimeters (cc), stationary type, two cylinders, an air cooled feature and B10 (90% diesel and 10% palm biodiesel), using a test bench to improve statistically the repeatability and reproducibility of the runs. The experimental reference tests were carried out under defined conditions at a fixed speed of 1800 revolutions per minute (rpm) and four load levels: 35%, 50%, 65% and 80%. The repeatability analysis was based on the technical standard NTC-ISO / IEC17025. The variables of torque, fuel consumption (FC), air consumption (AC) and exhaust gas temperatures (EGT) showed an increase related with the load increase, showing a lower variation of AC and emissions. With the mechanism’s implementation of attenuator of air blows, adjustment mechanism for rpm and preheating air chamber for intake manifold, it was observed that the rpm presented the lowest statistical variability. The variables that presented the highest Pearson correlation with respect to the FC are the CO₂, NO_X and O₂, this is because the engine does not have the Common Rail system, which causes the fuel supply to not be injected accurately and uniformly, therefore the evaluation of performance of the engine could not be repeatable.

Global fossil fuel consumption, including diesel and gasoline, significantly contributes to emissions. Understanding emission percentages and types is critical. Alternative energies, like hydrogen mixed with gasoline, help mitigate emissions in sectors such as transport and energy. Hydrogen-gasoline blends in internal combustion engines improve the combustion process but require studying engine behavior and carbon footprint. This research designs a low-cost sensor network to monitor combustion emissions and provide reliable data for statistical comparison across vehicles. Two synchronized client–server software systems are proposed. The client software runs on an IoT development board (ESP32) and communicates with sensors via the ESP-NOW protocol to detect and collect gas data, transmitting it wirelessly to the web server. The server software provides a user-friendly interface for data control and visualization from a ground station. Tests used 100% Mexican gasoline (G100) and hydrogen-gasoline blends (GH) with a hydrogen cell electrolyte concentration of 0.0211 mL/gal (80 mL). A single vehicle followed the same route at 40–60 km/h, collecting data every 30 s over three trials. Results showed average reductions of 5% and 10% in CO and CO₂ emissions, respectively, with GH fuel.

The global consumption of fossil fuels such as diesel and gasoline represent a considerable per-centage of global emissions, it is important to know for sure the percentage and type of gas emitted, there are many alternative energies that mitigate the production of emissions in different sectors such as the transport sector and the energy sector. The percentage use of hydrogen mixed with gasoline in internal combustion engines is a viable alternative because it helps the com-bustion process, but it is necessary to know the behavior of the engine and determine the carbon footprint, to quantify the benefit of these actions it is necessary to design and implement a network of low-cost sensors that monitor the emissions produced during the combustion processes and provide reliable data that can be used to make a statistical comparison between vehicles. This research proposes two software systems of an architecture (client-server) working in a synchro-nized manner in order to collect and store information in a database. The first software works as the client and runs on an IoT development board called ESP32 in conjunction with esp32 ttgo and communication between both devices is done through the esp now protocol, this software estab-lishes the connection with the physical sensors to detect and collect gas information, the data is sent wirelessly to the web server, the second software works as a server in addition to providing a graphical interface for user control and data visualization from a ground station. The tests were carried out using 100% Mexican gasoline (G100) and a mixture of hydrogen fuel with gasoline (GH) for the hydrogen cell a concentration of 0.0211 ml / gal of electrolytes (80 ml) was used, the same route and vehicle were used at an average acceleration of 40 and 60 km / h, the data obtained are taken every 30 seconds, the process was repeated 3 times and an average emission reduction of 5% and 10% of CO and CO2 respectively was obtained with GH fuel.