Abstract
Most human time is spent indoors, and due to the pandemic, monitoring indoor air quality (IAQ) has become more crucial. In this study, an IoT (Internet of Things) architecture is implemented to monitor IAQ parameters, including CO2 and particulate matter (PM). An ESP32-C6-based device is developed to measure sensor data and send them, using the MQTT protocol, to a remote InfluxDBv2 database instance, where the data are stored and visualized. The Python 3.11 scripting programming language is used to automate Flux queries to the database, allowing a more in-depth data interpretation. The implemented system allows to analyze two measured scenarios during sleep: one with the door slightly open and one with the door closed. Results indicate that sleeping with the door slightly open causes CO2 levels to ascend slowly and maintain lower concentrations compared to sleeping with the door closed, where CO2 levels ascend faster and the maximum recommended values are exceeded. This demonstrates the benefits of ventilation in maintaining IAQ. The developed system can be used for sensing in different environments, such as schools or offices, so an IAQ assessment can be made. Based on the generated data, predictive models can be designed to support decisions on intelligent natural ventilation systems, achieving an optimized, efficient, and ubiquitous solution to moderate the IAQ.

Abstract
The autonomous navigation of unmanned ground vehicles (UGVs) in unstructured environments, such as agricultural or forestry settings, has been the subject of extensive research by various investigators. The navigation capability of a UGV in unstructured environments requires considering numerous factors, including the quality of data reception that allows reliable interpretation of what the UGV perceives in a given environment, as well as the use these data to control the UGV's navigation. This article aims to study different PID control algorithms to enable autonomous navigation on a robotic platform. The robotic platform consists of a forestry tractor, used for forest cleaning tasks, which was converted into a UGV through the integration of sensors. Using sensor data, the UGV's position and orientation are obtained and utilized for navigation by inputting these data into a PID control algorithm. The correct choice of PID control algorithm involved the study, analysis, and implementation of different controllers, leading to the conclusion that the Vector Field control algorithm demonstrated better performance compared to the others studied and implemented in this paper.

Abstract
Pharmaceuticals have emerged as contaminants in aquatic ecosystems, challenging the water quality concept. These compounds enter wastewater treatment plants, where inefficient treatments pose concerns for long-term river and tap water quality, consequently impacting environmental and human health. Considering this, the present study first reports the simultaneous quantification of paracetamol, salicylic acid, and carbamazepine by electrochemistry with carbon screen-printed electrodes, as well as liquid chromatography-tandem mass spectrometry (LC-MS/MS). At pH 7.4 and by optimized DPV, LODs were 0.783, 1.53, and 0.113 mu M for paracetamol, salicylic acid, and carbamazepine, respectively. The recovery values obtained by LC-MS/MS in tap water are not satisfactory regarding the data obtained in river water with DPV electrochemical experiments. Moreover, in both analytical methods, the highest sensitivity was obtained for carbamazepine, with the lowest RSD values. These analytical data highlight the remarkable sensitivity and detection skills of DPV and LC-MS/MS analysis. Developing portable potentiostats for in situ pharmaceutical detection and monitoring outside the labs is crucial for ensuring environmental and health safety. Herein two portable approaches are tested: commercial SensitSmart (R) and homemade electrochemical Internet-of-Things (IoT)-enabled devices. The results of SensitSmart (R) are reliable but lower than those obtained with a benchtop potentiostat and require a USB connection with PCs, tablets, or smartphones. The practical application of a homemade IoT device was validated with potassium ferricyanide with an output similar to benchtop potentiostat, which represents a proof of concept. In the future, these IoT devices will operate without external components or specific software.

Abstract
The efficiency of wastewater treatment systems must be reflected in the removal of the pollutant load from the influent and the optimal energy performance of electrical equipment. Wastewater Treatment Plants (WWTPs) are part of the Intensive Energy Consumption Management System (SGCIE) and are therefore subject to mandatory energy audits. This article aims to assess the impact of an energy audit in a WWTP, according to ISO 50001:2018 and the Plan-Do-Check-Act (PDCA) methodology, to identify and quantify both persistent and transient energy inefficiencies. According to the results, the energy audit contributed to an approximate 10.8% reduction in electrical energy consumption. During the assessment, several challenges were identified that may compromise the effectiveness of audits in improving energy performance. The complexity of the treatment model, aging infrastructure and equipment, the lack of real-time data, and a limited number of indicators hinder the proper management of inefficiency phenomena, particularly transient ones.

Abstract
Road safety is a global issue, with road-related accidents being one of the biggest leading causes of death. Motorcyclists are especially susceptible to injuries and death when there is an accident, due to the inherent characteristics of motorcycles. Accident prevention is paramount. To improve motorcycle safety, this paper discusses and proposes a preliminary architecture of a system composed of various sensors, to assist and warn the rider of potentially dangerous situations such as front and back collision warnings, pedestrian collision warnings, and road monitoring.

Abstract