Browsing by Author "Asorey Cacheda, Rafael"
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Item An Intelligent Auditory and Visual Stimulation System for Indoor Spaces: Human Biosignals in Response to Stimuli(Korea Information Processing Society, 2025) Alvarez Garcia, Gonzalo Alberto; Zúñiga Cañón, Claudia Liliana; Garcia Sanchez, Antonio Javier; Garcia Haro, Joan; Asorey Cacheda, RafaelIn the age of digitalization, merging artificial intelligence (AI) and Internet of Things (IoT) has ushered in groundbreaking systems capable of impacting human behavior. This paper focuses on a system that integrates AIoT technology and explores its impact on human emotions and behavior to enhance human experiences in indoor spaces. The study developed a system that orchestrates a series of auditory and visual cues and monitors brain and cardiac responses to identify the effectiveness of audio–visual stimuli. AI algorithms enable us to comprehend and recommend actions concerning the stimuli within the civil infrastructure, thereby influencing individual and group behavior. The proposed system produces auditory stimuli, such as music or ambient sounds, along with visual stimuli, such as lighting and information systems. The system collected electroencephalogram (EEG) and electrocardiogram (ECG) signals to validate the capacity of these stimuli. This technological integration empowered the system to adjust to the needs of individuals and groups, thus enhancing the indoor experience. The study focused on identifying EEG responses in the late positive potential (LPP) and their correlation with ECG responses, particularly within LPP as an EEG component, as it relates to decision-making and emotional perception. By determining the LPP, the system can tailor auditory and visual stimulation to enhance user experience. This system has applications for enhancing learning, public space comfort, and mental well-being. Through adjusting auditory and visual stimulation based on biometric signals, the system can foster a more comfortable environment for concentration, productivity, or relaxation. Despite its potential, the system presents challenges such as individual variability and the need for clinical validation. Furthermore, ethical and privacy considerations must be addressed to prevent the use of invasive technologies. In conclusion, the proposed system is a significant advancement in the intersection of AIoT technology and its influence on biological processes. While challenges remain, the system’s capacity to enrich the human experience in indoor settings is promising.Item Artificial Intelligence of Behavior for Human Emotion Recognition in Closed Environments(Institute of Electrical and Electronics Engineers Inc., 2024) Alvarez Garcia, Gonzalo Alberto; Zuniga Canon, Claudia; Garcia Sanchez, Antonio Javier; Garcia Haro, Joan; Sarria Paja, Milton; Asorey Cacheda, RafaelUnderstanding human emotions and behavior in closed environments is essential for creating more empathetic and humane spaces. Environmental factors, such as temperature, noise, and light, play a crucial role in influencing behavior, but individuals' emotional states are equally important and often go unnoticed. Artificial Intelligence of Behavior (AIoB) offers a novel approach that integrates environmental measurements with human emotions to create spatially adaptive processes that can influence behavior. In this article, we present a new human emotion sensor developed using video cameras and implemented on a System on Chip (SoC) development board. Our approach uses Convolutional Neural Networks (CNNs) to recognize the presence of emotions in enclosed spaces and generate parameters that can influence emotional states and behavior within an AIoB system. The research successfully integrates advanced CNN technology into a System on Chip (SoC) platform, allowing for real-time processing of video data. The versatility of utilizing an energy-efficient SoC extends its application to smart environments aimed at improving mental health. By employing algorithms capable of detecting emotional states across various individuals, the study enhances its effectiveness. Additionally, it identifies the best CNN operations tailored to the technical specifications of the devices involved. Thus, The development involves a three-step process: (i) collecting enough data to build a robust model, (ii) training the model and evaluating its performance using test values, and (iii) applying the model on the development board. Our study demonstrates the feasibility of using AIoB to recognize and respond to human emotions in closed areas. By integrating emotional cues with environmental measurements, our system can create more personalized and empathetic spaces that cater to the needs of individuals. Our approach could have significant implications for designing public spaces to promote well-being and emotional satisfaction.Item Crowdsourcing Optimized Wireless Sensor Network Deployment in Smart Cities: A Keynote(Springer Verlag, 2019-02-21) Asorey Cacheda, Rafael; Garcia Sanchez, Antonio Javier; Zúñiga Cañón, Claudia; Garcia Haro, JoanThe deployment of wireless sensor networks in smart cities for environmental monitoring is a complex issue. One of the main problems is to determine the most appropriate places for these tasks. This paper proposes the use of information from crowdsourcing to identify places of interest from the environmental point of view to deploy the sensor network.Item Lightweight Blockchain for Data Integrity and Traceability in IoT Networks(Institute of Electrical and Electronics Engineers Inc., 2026-05-07) García, Laura; Cancimance, Carlos; Asorey Cacheda, Rafael; Zúñiga Cañón, Claudia Liliana; Garcia Sanchez, Antonio Javier; Garcia Haro, JoanData integrity and traceability are important challenges to provide security in the Internet of Things (IoT) networks, which are often vulnerable to data manipulation attacks due to their use of low-resource devices and wireless communication technologies. In this regard, blockchain is a promising solution to enhance IoT security, but the implementation of a conventional blockchain requires high computational and network connectivity resources that are not compatible with IoT networks. In this paper, we propose a lightweight blockchain for data integrity and traceability in IoT networks that adapts the Distributed Ledger Technology (DLT) feature of blockchain to the LoRaWAN wireless communication protocol. Our proposal offers data integrity without the need for complex consensus algorithms or cryptographic operations. We also have designed and implemented a logical LoRaWAN P2P topology that enables communication between the IoT nodes which comprise LoRaWAN’s characteristic star topology. Finally, we evaluate our proposal and demonstrate its feasibility and performance in terms of data traceability, and network overhead.Item Optimizing Ambiance: Intelligent RGB Lighting Control in Structures Using Fuzzy Logic(MDPI, 2024) Alvarez Garcia, Gonzalo Alberto; Zúñiga Cañón, Claudia Liliana; Garcia Sanchez, Antonio Javier; Garcia Haro, Joan; Asorey Cacheda, RafaelManaging red–green–blue (RGB) lighting conditions within structures may evoke emotions and positively influence behavior. Intelligent RGB lighting systems based on environmental data measurements can substantially enhance the perception of comfort. This study presents a challenge that requires a holistic and integrated approach to implement an automatic RGB artificial lighting control system that can be utilized in various structures and indoor environments. Initially, the challenge spans the identification of environmental variables directly impacting comfort up to the careful selection of suitable sensors. The result is the development of a sophisticated and autonomous system that can adjust RGB lighting in real time, creating environments that are both comfortable and energy-efficient. This automated system fosters the creation of appropriate atmospheres across different contexts. The identification and monitoring of environmental variables are achieved through a neuro-fuzzy control mechanism, where fuzzy rules and membership functions are defined based on late positive potential timings and the influence of artificial lighting on human emotions. The outcomes from this study are an interconnected system capable of performing both online and offline operations to enable the monitoring of environmental variables and the efficient management of artificial lighting based on these metrics. A pilot study, with reference to an EEG wave registry system, yielded significant results. These tests had a statistically relevant result with an average frequency of approximately 9.8 Hz, indicative of a state of comfort among people. Despite a 10% deviation margin, 87% of measurements during the test remained consistent. This research study contributes to human behavior by fostering a relaxing environment and enabling a reduction in energy consumption through the use of efficient lighting. Moreover, the environment intention enables the creation of stimuli in three emotional states: activation, relaxation, and neutral, allowing behavioral adaptation to an intention to occur automatically in fluctuating environmental conditions.Item Procedural modeling applied to the 3D city model of bogota: a case study(2021) Alomía, Gustavo; Loaiza, Diego; Zúñiga, Claudia; Luo, Xun; Asorey Cacheda, RafaelBackground Computer Generated Animations (CGA), when applied to three-dimensional (3D) city models (3DCM), can be used as powerful tools to support urban decision-making. This leads to a new paradigm, based on procedural modeling, that allows the integration of known urban structures. This paper introduces a new workflow for the development of high-quality approximations of urban models in a short time and enables facilities to be imported from other cities into a given city model, following specific generation rules. Thus, this workflow provides a very simple approach to observe, study, and simulate the implementation of models already developed in other cities, in a city where they are not yet adopted. Examples of these models include all types of mobility systems and urban infrastructure. This allows us to perceive the environmental impact of certain decisions in the real world, as well as to carry out simple simulations to determine the changes that can occur in the flows of people, traffic, and other city activities.Item Sistema de instrumentación y control de estimulación auditivo y visual con tecnología AIoT para regular el comportamiento(Universidad Santiago de Cali, 2024-09-30) Álvarez García, Gonzalo Alberto; Asorey Cacheda, Rafael; Zúñiga Cañón, Claudia LilianaThe instrumentation and control systems have allowed the analysis of various systems that touch all aspects of science, developing an evolutionary connection with the needs of human beings and their context, the revolution in the field of biology, industry are just some examples of these scopes. In addition, technologies based on IoT (Internet of Things) systems have interconnected the different devices of our lives, from the simplest thing like turning on or off a light bulb, to being able to control the temperature and humidity of our living spaces. Nowadays, the new reality has posed a new restart to social situations, environments, meeting spaces have suffered due to the situation of the COVID - 19 pandemic, these spaces have not had significant transformations, although our personal spaces, some of them mediated by technology, have been transformed, the conditions in spaces of social interaction have not had an adequate evolution to the technological elements they have. This difference between personal and social spaces has generated a need in which environments and environments must become agents with the capacity to interact with people and to allow both participants and administrators of the spaces a possibility to regulate people’s attitudes and evoke activating or relaxing behaviors. The objective of the work proposed here is to design and build an instrumentation and control system recording the environmental conditions of the environment and generate an auditory and visual stimulus, as a regulatory agent of the environment, with elements of the IoT with robust and accessible technology for the integration of systems for monitoring and control online and also its autonomous operation.Item Smart Air Quality Monitoring IoT-Based Infrastructure for Industrial Environments(2022-12) García, Laura; Garcia Sanchez, Antonio-Javier; Asorey Cacheda, Rafael; Garcia Haro, Joan; Zúñiga Cañón, Claudia-LilianaDeficient air quality in industrial environments creates a number of problems that affect both the staff and the ecosystems of a particular area. To address this, periodic measurements must be taken to monitor the pollutant substances discharged into the atmosphere. However, the deployed system should also be adapted to the specific requirements of the industry. This paper presents a complete air quality monitoring infrastructure based on the IoT paradigm that is fully integrable into current industrial systems. It includes the development of two highly precise compact devices to facilitate real-time monitoring of particulate matter concentrations and polluting gases in the air. These devices are able to collect other information of interest, such as the temperature and humidity of the environment or the Global Positioning System (GPS) location of the device. Furthermore, machine learning techniques have been applied to the Big Data collected by this system. The results identify that the Gaussian Process Regression is the technique with the highest accuracy among the air quality data sets gathered by the devices. This provides our solution with, for instance, the intelligence to predict when safety levels might be surpassed.