Sistema de control y monitoreo de consumo energético para equipos de climatización orientado a internet de las cosas (IOT)

Maestría en IngenieríaHVAC systems (Heating, Ventilating and Air Conditioning) consume 40% of total domestic energy, with more than 25% of energy demand in homes and offices in Colombia. According to what has been studied in the state of the art, there are various factors that influence the efficiency of these systems. Some of the factors that influence the behavior of air conditioning systems are: the efficiency inherent to the manufactured system (intrinsic characteristics), the environmental conditions of each region (extrinsic conditions, such as external temperature), the responsible use by the end users, and the perception of comfort on the part of the occupants of the enclosure where the system operates, among others. This research addresses the problem of energy consumption of HVAC systems, from the view of rational consumption based on their operating conditions. The above implies to analyze and correlate the behavior of HVAC systems with changes in the behavior of environmental (external) temperature conditions. In addition, integrate control and monitoring solutions to the Internet of Things (IoT) technologies to manage valuable information based on real time data analysis. Thus, this document summarizes the development of a control system and monitoring of energy consumption for an air conditioning (AC) system oriented to IoT. With the implementation of IoT-based technologies, a significant contribution is made to the monitoring tools, data acquisition and therefore, monitoring for the evaluation of the control techniques of these systems. The monitoring action generates large amounts of data that may be of interest to users, researchers or distribution and marketing companies of air conditioning systems. The document defines the requirements and control techniques for the development of an embedded device using an architecture based on the MQTT protocol applied to the air conditioning system. As well as the stages considered during the implementation in a conventional mini-split HVAC system are described. Finally, the results of the control and monitoring system are compared with the data of the same system without the embedded device in order to validate operation, implementation and integration ith the systemLos sistemas de climatización, o HVAC por sus siglas en inglés (Heating, Ventilating and Air Conditioning), consumen el 40% de la energía domestica total, siendo para Colombia más del 25% de la demanda energética en hogares y oficinas. De acuerdo a lo estudiado en el estado del arte, son diversos los factores que influyen en la eficiencia de estos sistemas. Algunos estos de los factores que influyen en el comportamiento de los sistemas de climatización son: la eficiencia propia del sistema fabricado (características intrínsecas), las condiciones ambientales de cada región (condiciones extrínsecas, como la temperatura externa), el uso responsable por parte de los usuarios finales, y la percepción del confort por parte de los ocupantes del recinto donde opera el sistema, entre otras. En esta investigación se aborda la problemática del consumo energético de los sistemas HVAC, desde la visión del consumo racional basado en las condiciones de funcionamiento de los mismos. Lo anterior, implica analizar y correlacionar el comportamiento de los sistemas HVAC con los cambios en el comportamiento de las condiciones de la temperatura del medio ambiente (externa). Además, integrar soluciones de control y monitoreo a las tecnologías de internet de las Cosas (IoT) para gestionar información valiosa a partir del análisis de datos en tiempo real. Es así que, el presente documento resume el desarrollo de un sistema de control y monitoreo de consumo energético para un sistema de aire acondicionado (AC) orientado a IoT. Con la implementación de tecnologías basadas en IoT se logra un aporte significativo a las herramientas de monitoreo, adquisición de datos y por ende, de seguimiento para la evaluación de las técnicas de control de estos sistemas. La acción de monitoreo genera grandes cantidades de datos que pueden interesarle a los usuarios, investigadores o empresas distribuidoras y comercializadoras de sistemas de climatización. Dentro del documento se definen los requisitos y técnicas de control, para el desarrollo de un dispositivo embebido usando una arquitectura basada en el protocolo MQTT aplicada al sistema de climatización. Al igual que se describen las etapas consideradas durante la implementación en un sistema HVAC tipo mini-split convencional. Finalmente, los resultados del sistema de control y monitoreo son comparados con los datos del mismo sistema sin el dispositivo embebido a fin de validar funcionamiento, implementación e integración con el sistem

Stochastic performance indices to infer deterministic indices through machine learning in the performance analysis of control loops

Control loops are the most critical components in many production processes. In this process, the economic yield is strongly linked to the performance of the control loops since aspects such as safety conditions, process quality, and energy and raw material consumption depend on this. However, experience has shown that most of the control loops can be improved by identifying and correcting the causes of the poor perfor-mance. The indices to evaluate the performance of the control loops can be divided into two groups, stochastic and deterministic. The most known of the former is the minimum variance index. Stochastic indices only require data collected under normal operating conditions and minimum knowledge of the process, making it possible to evaluate performance online. However, some disadvantages, such as scale and span problems, make performance analysis difficult. The deterministic indices (rise time, settling time, overshoot, phase and gain margins, etc.) are easy to interpret, facilitating the analysis; however, invasive plant tests are necessary to estimate them, making them impractical. Is it possible to link these two approaches? With that question in mind, in this work, it is proposed to build a model to estimate deterministic indices (to evaluate robustness and performance of control loops), considering stochastic indices and some process information as model inputs. This paper shows the procedure to build the inferential model by using machine learning techniques

Patients and healthcare professionals’ voice on preventable readmissions

Introduction Currently, about 10% of patients required unplanned readmissions within 30 days after discharge.1 2 This proportion has not changed substantially over the past several years despite intense efforts to improve the discharge process. Although several studies3 4 have been performed, including patients’ and physicians’ opinion on the preventability of readmissions and factors that would predict preventability, only a few studies have included nurses’ opinions and the consensus with all stakeholders.5 We aimed to determine the patient’s opinion on preventable readmission, associated factors and the extent to which patients, nurses and physicians agree on readmission preventability. Methods To achieve the proposed objectives, a descriptive transversal correlational multicentre study was developed. This study was approved by the Clinical Research Ethics Committee (reference number: PR114/17). From 2 April 2017 to 18 January 2019, all patients readmitted within 30 days to 2 medical and 2 surgical departments (internal medicine, pneumology, trauma and digestive surgery) at 4 university hospitals were identified. Patients who provided written informed consent were interviewed within 72 hours of readmission. Four research nurses were trained to deliver the interviews. The patient’s interview involved 23 questions6 about functional status at discharge, discharge process and follow-up care, including readmission preventability (online supplemental material). Two independent physicians and nurses of the research team concurrently reviewed electronic health records to identify factors contributing to potentially preventable readmissions.7 Clinical and demographic patients’ characteristics were also collected. We estimated that a total sample size of 276 patients was needed for a proportion of 11% of preventable readmission,7 95% confidence level and 0.04 precision and assuming 15% potentially missed cases. A logistic regression model has been used to assess the association between the patient profile and his answer to the main question of his readmission preventability. The conditions of application of the models have been validated and CIs at 95% of the estimator have been calculated whenever possible. Cohen’s kappa statistic has been calculated to assess the concordance between physicians’, nurses’ and patients’ answer to this preventability readmission question. All the analysis has been done with the statistic package R V.3.5.3 (11 March 2019) for Windows. Patients were not involved in the design, conduct, reporting or dissemination plans of this study. Results We assessed 805 consecutive patients for eligibility, of whom 529 were excluded refused or unavailable (314 presented haemodynamic instability, 107 were discharged early, 104 refused to participate and four had language barrier). Among 276 patients included, 44.2% were admitted to internal medicine, 13.8% pneumology, 8% trauma and 34.1% digestive surgery department, respectively. The mean age was 68 years and 65.9% were men. The median (IQR) time between discharge and readmission was 11 days (5–17 days) and the median (IQR) Charlson comorbidity index was 5 (3–6). Ninety-six (34.8%) patients reported that their readmission was preventable, 69 (25.0%) were undecided and 111 (40.2%) reported that their readmission was not preventable. Comparing patients who reported non-preventable readmissions to those who reported preventable readmissions or were undecided, the latter had less time between discharge and readmission, did not have a follow-up appointment scheduled with primary care or specialist at discharge, no medication reviewed and felt concerns were not addressed before discharge. Also, patients who were less satisfied with the hospital’s discharge team, who felt were discharged before being ready and felt concern during follow-up care were more likely to report preventable readmission or undecidednes

Model Predictive Control Strategies Performance Evaluation over a Pipeline Transportation System

In several industries using pipelines to transport different products from one point to another is a common and indispensable process, especially at oil/hydrocarbon industries. Thus, optimizing the way this process is carried out must be an issue that cannot be stopped. Therefore, the performance of the control strategy implemented is one way of reaching such optimal operating zones. This study proposes using Model Predictive Control strategies for solving some issues related to the proper operation of pipelines. It is proposed a model based on physics and thermodynamic laws, using MATLAB® as the development environment. This model involves four pumping stations separated by three pipeline sections. Three MPC strategies are developed and implemented. Accordingly, the results indicate that a centralized controller with an antiwindup back-calculation method has the best results among the three configurations used

Chemical and nano-mineralogical study for determining potential uses of legal Colombian gold mine sludge: Experimental evidence

The present study is focused on the chemical and nano-mineralogical characterization of sludge from gold mine activities, in order to put forward diverse solution alternatives, where lack of knowledge has been found. The sample was collected from “La Estrella” mine of Suarez, located in Department of Cauca, south-west Colombia. The sludge micro-structure and chemical composition were analyzed using a high resolution transmission electron microscopy (HR-TEM) equipped with a dispersive X-ray detector (EDS). X-ray diffraction technique was employed to identify the mineralogical phases present in the sludge. Additional mineralogical characterization was done by using RAMAN spectroscopy. Main findings points to its potential to be used as a fertilizer, this is why, mine sludge contains macronutrients such as P, Ca and S, together with micronutrients like Cu. However, the presence of goethite could decrease the mobilization of nutrients to soils, thus additional alternatives, for instance, a mixture with humus or another material containing Humic Acids should be done, in order to minimizing its retention effect. Additionally, another possible uses to explore could be as construction and ceramic material or in the wastewater treatment for nutrient retention and organic material removal. Rutile (TiO2 nanoparticles) particles have been also detected, what could cause health concern due to its nanoparticle toxic character, mainly during gold extraction process

Post-Hospital Syndrome and Hyponatremia

Introduction: Post-hospital syndrome (PHS) is defined as a period of vulnerability during the first 30 days after a patient is discharged from hospital, in which multiple factors come into play. Hyponatremia is the most frequent hydroelectrolytic disorder in hospitalized patients and may be related to the appearance of PHS. Objective: The objective is to estimate the prevalence of PHS that is assessed as the rate of readmissions in the first 30 days after discharge, in patients with hyponatremia. Material and Methods: It is a descriptive observational study of patients with hyponatremia who were discharged from 1 September 2010 to 2 February 2020 at the Internal Medicine Service of the Hospital University of San Juan (Alicante, Spain). Results: Of the 25 included patients, 5 (20%) were readmitted within a month of discharge, after a mean of 11.4 days (standard deviation [SD] 5.1). The overall mortality of the study was 20% (n = 5), with one case of death in the first 30 days post-hospitalization (4%). In 12 patients (48%) the origin of the hyponatremia was undetermined. The most frequently recorded etiology for the condition was pharmacological (n = 7, 28%), and there was pronounced variability in its clinical and laboratory study. The most widely used corrective measure was drug withdrawal, in 16 patients (64%). Water intake restriction was the most common treatment after discharge (5 patients, 20%), followed by urea (2 patients, 8%), while tolvaptan was not used. Conclusion: Hyponatremia may be the cause of PHS, which could increase the rate of early readmission. Hyponatremia is an underdiagnosed and undertreated entity, so it is necessary to apply an appropriate system to optimize its management and, in future studies, to assess its impact on PHS

Antithrombotic Therapy in Elderly Patients with Acute Coronary Syndromes

The treatment of acute coronary syndrome (ACS) in elderly patients continues to be a challenge because of the characteS.G.B.ristics of this population and the lack of data and specific recommendations. This review summarizes the current evidence about critical points of oral antithrombotic therapy in elderly patients. To this end, we discuss the peculiarities and differences reported referring to dual antiplatelet therapy (DAPT) in ACS management in elderly patients and what might be the best option considering these population characteristics. Furthermore, we analyze antithrombotic strategies in patients with atrial fibrillation (AF), with a particular focus on those cases that also present coronary artery disease (CAD). It is imperative to deepen our knowledge regarding the management of these challenging patients through real-world data and specifically designed geriatric studies to help resolve the questions remaining in their disease management