Velázquez, Ramiro
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Preferred name
Velázquez, Ramiro
Official Name
Velázquez Guerrero, Ramiro
Alternative Name
rvelazquez
Main Affiliation
ORCID
Scopus Author ID
7003505296
Researcher ID
GQW-6348-2022

Research Output
Now showing 1 - 10 of 31
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Self-powered WiFi-connected monitoring stations for environmental pollution app-based control in urban and industrial areas

2022 , Paolo Visconti , Roberto de Fazio , Velázquez, Ramiro , Bassam Al-Naami , Amir Aminzadeh Ghavifekr

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Modeling and Prototype Implementation of an Automated Guided Vehicle for Smart Factories

2021 , Hiroki Sasamoto , Velázquez, Ramiro , Manuel Cardona , Gutiérrez, Sebastián , Amir A. Ghavifekr , Paolo Visconti

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Available Technologies and Commercial Devices to Harvest Energy by Human Trampling in Smart Flooring Systems: A Review

2022 , Paolo Visconti , Laura Bagordo , Ramiro Velázquez , Donato Cafagna , Roberto De Fazio

Technological innovation has increased the global demand for electrical power and energy. Accordingly, energy harvesting has become a research area of primary interest for the scientific community and companies because it constitutes a sustainable way to collect energy from various sources. In particular, kinetic energy generated from human walking or vehicle movements on smart energy floors represents a promising research topic. This paper aims to analyze the state-of-art of smart energy harvesting floors to determine the best solution to feed a lighting system and charging columns. In particular, the fundamentals of the main harvesting mechanisms applicable in this field (i.e., piezoelectric, electromagnetic, triboelectric, and relative hybrids) are discussed. Moreover, an overview of scientific works related to energy harvesting floors is presented, focusing on the architectures of the developed tiles, the transduction mechanism, and the output performances. Finally, a survey of the commercial energy harvesting floors proposed by companies and startups is reported. From the carried-out analysis, we concluded that the piezoelectric transduction mechanism represents the optimal solution for designing smart energy floors, given their compactness, high efficiency, and absence of moving parts.

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An Energy Model Using Sleeping Algorithms for Wireless Sensor Networks under Proactive and Reactive Protocols: A Performance Evaluation

2020 , Del-Valle-Soto, Carolina , Velázquez, Ramiro , Valdivia, Leonardo , Nicola Ivan Giannoccaro , Paolo Visconti

The continuous evolution of the Internet of Things (IoT) makes it possible to connect everyday objects to networks in order to monitor physical and environmental conditions, which is made possible due to wireless sensor networks (WSN) that enable the transfer of data. However, it has also brought about many challenges that need to be addressed, such as excess energy consumption. Accordingly, this paper presents and analyzes wireless network energy models using five different communication protocols: Ad Hoc On-Demand Distance Vector (AODV), Multi-Parent Hierarchical (MPH), Dynamic Source Routing (DSR), Low Energy Adaptive Clustering Hierarchy (LEACH) and Zigbee Tree Routing (ZTR). First, a series of metrics are defined to establish a comparison and determine which protocol exhibits the best energy consumption performance. Then, simulations are performed and the results are compared with real scenarios. The energy analysis is conducted with three proposed sleeping algorithms: Modified Sleeping Crown (MSC), Timer Sleeping Algorithm (TSA), and Local Energy Information (LEI). Thereafter, the proposed algorithms are compared by virtue of two widely used wireless technologies, namely Zigbee and WiFi. Indeed, the results suggest that Zigbee has a better energy performance than WiFi, but less redundancy in the topology links, and this study favors the analysis with the simulation of protocols with different nature. The tested scenario is implemented into a university campus to show a real network running.

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An Efficient Point-Matching Method Based on Multiple Geometrical Hypotheses

2021 , Miguel Carrasco , Domingo Mery , Andrés Concha , Velázquez, Ramiro , Roberto De Fazio , Paolo Visconti

Point matching in multiple images is an open problem in computer vision because of the numerous geometric transformations and photometric conditions that a pixel or point might exhibit in the set of images. Over the last two decades, different techniques have been proposed to address this problem. The most relevant are those that explore the analysis of invariant features. Nonetheless, their main limitation is that invariant analysis all alone cannot reduce false alarms. This paper introduces an efficient point-matching method for two and three views, based on the combined use of two techniques: (1) the correspondence analysis extracted from the similarity of invariant features and (2) the integration of multiple partial solutions obtained from 2D and 3D geometry. The main strength and novelty of this method is the determination of the point-to-point geometric correspondence through the intersection of multiple geometrical hypotheses weighted by the maximum likelihood estimation sample consensus (MLESAC) algorithm. The proposal not only extends the methods based on invariant descriptors but also generalizes the correspondence problem to a perspective projection model in multiple views. The developed method has been evaluated on three types of image sequences: outdoor, indoor, and industrial. Our developed strategy discards most of the wrong matches and achieves remarkable F-scores of 97%, 87%, and 97% for the outdoor, indoor, and industrial sequences, respectively.

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A remote-controlled global navigation satellite system based rover for accurate video-assisted cadastral surveys

2022 , Paolo Visconti , Marzia Luceri , Velázquez, Ramiro , De Fazio Roberto

<span>One of the main tasks of a cadastral surveyor is to accurately determine property boundaries by measuring control points and calculating their coordinates. This paper proposes the development of a remotely-controlled tracking system to perform cadastral measurements. A Bluetooth-controlled rover was developed, including a Raspberry Pi Zero W module that acquires position data from a VBOX 3iSR global navigation satellite system (GNSS) receiver, equipped with a specific modem to download real-time kinematic (RTK) corrections from the internet. Besides, the Raspberry board measures the rover speed with a hall sensor mounted on a track, adjusting the acquisition rate to collect data at a fixed distance. Position and inertial data are shared with a cloud platform, enabling their remote monitoring and storing. Besides, the power supply section was designed to power the different components included in the acquisition section, ensuring 2 hours of energy autonomy. Finally, a mobile application was developed to drive the rover and real-time monitor the travelled path. The tests indicated a good agreement between rover measurements and those obtained by a Trimble R10 GNSS receiver (+0.25% mean error) and proved the superiority of the presented system over a traditional metric wheel.</span>

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Linear and Nonlinear Control Approaches for the Cart Inverted Pendulum Problem

2021 , Enrique Preza , Velázquez, Ramiro , Macías-Quijas, Ricardo , Hernandez, Erika , Paolo Visconti

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Enhancing Elderly Care through Low-Cost Wireless Sensor Networks and Artificial Intelligence: A Study on Vital Sign Monitoring and Sleep Improvement

2024 , Del-Valle-Soto, Carolina , Ramon A. Briseño , Velázquez, Ramiro , Gabriel Guerra-Rosales , Santiago Perez-Ochoa , Isaac H. Preciado-Bazavilvazo , Paolo Visconti , José Varela-Aldás

This research explores the application of wireless sensor networks for the non-invasive monitoring of sleep quality and vital signs in elderly individuals, addressing significant challenges faced by the aging population. The study implemented and evaluated WSNs in home environments, focusing on variables such as breathing frequency, deep sleep, snoring, heart rate, heart rate variability (HRV), oxygen saturation, Rapid Eye Movement (REM sleep), and temperature. The results demonstrated substantial improvements in key metrics: 68% in breathing frequency, 68% in deep sleep, 70% in snoring reduction, 91% in HRV, and 85% in REM sleep. Additionally, temperature control was identified as a critical factor, with higher temperatures negatively impacting sleep quality. By integrating AI with WSN data, this study provided personalized health recommendations, enhancing sleep quality and overall health. This approach also offered significant support to caregivers, reducing their burden. This research highlights the cost-effectiveness and scalability of WSN technology, suggesting its feasibility for widespread adoption. The findings represent a significant advancement in geriatric health monitoring, paving the way for more comprehensive and integrated care solutions.

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An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring

2021 , Roberto De Fazio , Marco Stabile , Massimo De Vittorio , Velázquez, Ramiro , Paolo Visconti

The demand for wearable devices to measure respiratory activity is constantly growing, finding applications in a wide range of scenarios (e.g., clinical environments and workplaces, outdoors for monitoring sports activities, etc.). Particularly, the respiration rate (RR) is a vital parameter since it indicates serious illness (e.g., pneumonia, emphysema, pulmonary embolism, etc.). Therefore, several solutions have been presented in the scientific literature and on the market to make RR monitoring simple, accurate, reliable and noninvasive. Among the different transduction methods, the piezoresistive and inertial ones satisfactorily meet the requirements for smart wearable devices since unobtrusive, lightweight and easy to integrate. Hence, this review paper focuses on innovative wearable devices, detection strategies and algorithms that exploit piezoresistive or inertial sensors to monitor the breathing parameters. At first, this paper presents a comprehensive overview of innovative piezoresistive wearable devices for measuring user’s respiratory variables. Later, a survey of novel piezoresistive textiles to develop wearable devices for detecting breathing movements is reported. Afterwards, the state-of-art about wearable devices to monitor the respiratory parameters, based on inertial sensors (i.e., accelerometers and gyroscopes), is presented for detecting dysfunctions or pathologies in a non-invasive and accurate way. In this field, several processing tools are employed to extract the respiratory parameters from inertial data; therefore, an overview of algorithms and methods to determine the respiratory rate from acceleration data is provided. Finally, comparative analysis for all the covered topics are reported, providing useful insights to develop the next generation of wearable sensors for monitoring respiratory parameters.

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Efficient Balancing Optimization of a Simplified Slider-Crank Mechanism

2020 , Orvañanos-Guerrero, María T. , Acevedo, Mario , Nicola Ivan Giannoccaro , Paolo Visconti , Sánchez-Gómez, Claudia , Velázquez, Ramiro

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