Prevention of Falls from Heights in Construction Using an IoT System Based on Fuzzy Markup Language and JFML

The main cause of fatal accidents in the construction sector are falls from height (FFH) and the inappropriate use of a harness is commonly associated with these fatalities. Traditional methods, such as onsite inspections, safety communication, or safety training, are not enough to mitigate accidents caused by FFH associated with a poor management in the use of a harness. Although some technological solutions for the automated monitoring of workers could improve safety conditions, their use is not frequent due to the particularities of construction sites: complexity, dynamic environments, outdoor workplaces, etc. Then, the integration of expert knowledge with technology is a key issue. Fuzzy logic systems (FLS) and Internet of Things (IoT) present many potential benefits, such as real-time decisions being made based on FLS and data from sensors. In the current research, the development and test of an IoT system integrated with the Java Fuzzy Markup Language Library for FLS, to support experts’ decision making in FFH, is proposed. The proposal was checked in four construction scenarios based on working conditions with different levels of risk of FFH and obtained promising results.Universidad de Malaga Plan Propio-Universidad de MalagaSpanish GovernmentEuropean Commission RTI2018-098371-B-I0

JFML: A Java Library to Design Fuzzy Logic Systems According to the IEEE Std 1855-2016

Fuzzy logic systems are useful for solving problems in many application fields. However, these systems are usually stored in specific formats and researchers need to rewrite them to use in new problems. Recently, the IEEE Computational Intelligence Society has sponsored the publication of the IEEE Standard 1855-2016 to provide a unified and well-defined representation of fuzzy systems for problems of classification, regression, and control. The main aim of this standard is to facilitate the exchange of fuzzy systems across different programming systems in order to avoid the need to rewrite available pieces of code or to develop new software tools to replicate functionalities that are already provided by other software. In order to make the standard operative and useful for the research community, this paper presents JFML, an open source Java library that offers a complete implementation of the new IEEE standard and capability to import/export fuzzy systems in accordance with other standards and software. Moreover, the new library has associated a Website with complementary material, documentation, and examples in order to facilitate its use. In this paper, we present three case studies that illustrate the potential of JFML and the advantages of exchanging fuzzy systems among available softwareThis work was supported in part by the XXII Own Research Program (2017) of the University of Córdoba, in part by the Spanish Ministry of Economy and Competitiveness under Grants RYC-2016-19802 (Ramón y Cajal contract), TIN2017-84796-C2-1-R, TIN2014-56633-C3-3-R, TIN2014-57251-P, and TIN2015-68454-R, in part by the Andalusian Government under Grant P11-TIC-7765, in part by the Xunta de Galicia (accreditation 2016-2019), and in part by the European Union (European Regional Development Fund)

License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours

This paper describes a new method for License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours. Given an image is divided into several virtual regions sized 10×10 pixels, applying several performance algorithms within each virtual region, algorithms such as edge detection, histograms, and binary thresholding, etc. These results are used as inputs for a Genetic Neural Network, which provides the initial selection for the probable situation of the license plate. Further refinement is applied using active contours to fit the output tightly to the license plate. With a small and well–chosen subset of images, the system is able to deal with a large variety of images with real–world characteristics obtaining great precision in the detection. The effectiveness for the proposed method is very high (97%). This method will be the first stage of a surveillance system which takes into account not only the actual license plate but also the model of the car to determine if a car should be taken as a threat

Carbon and water footprint for the recycling process of expanded polystyrene (EPS) post-consumer waste

[Abstract] Plastic pollution of the natural environment is ubiquitous, and around 40% of all plastic waste produced globally is used in single-use products and only 9% is recycled. From this plastic waste, expandable polystyrene single-use products pose a major problem because of its great volume and low density. To abord this issue, the authors proposed a circular economy model for EPS post-consumer waste in 2019 through a case study with the help of one local plastic manufacturer. Although the idea of promoting circularity of this waste seems a priori to have a good impact on the environment, the process to reincorporate reused and/or recycled materials under the concept of CE have economic and environmental impacts on the environment that should be measured. To understand if a recycling process is truly beneficial to the environment, first we need to do a sustainability analysis, using sustainability indicators, such as Carbon Footprint (CF) and Water Footprint (WF). The objective of the present paper is to perform a sustainability analysis of the expandable polystyrene post-consumer recycling into resin pellets using CF and WF as sustainability indicators. We proposed three case scenarios considering an artisanal recycling with 2019 (A), and 2027 proposed electricity power mix (B), industrial recycling with current 2019 electricity power mix (C) and the use of virgin PS and its destination in landfill to compare. We measured the CO2 emissions and m3 of freshwater with the help of SimaPro 9.1 software. Overall, the total CO2 emissions for the case scenarios A and B are approximately 42% and 16% higher than scenario D, but scenario C exhibits a reduction of almost 50%. For the water depletion, scenarios A and B show very higher values than those of scenario D with 536% and 534%, respectively. Important to mention that scenario B presents much better values for CF than scenario A, meaning that the increase in the share of electricity production by renewable energies can improve the sustainable production of recycled PS resin

Applying STEAM in a Smart City Environment with Internet of Things as A Learning Methodology Based on Projects

Con este artículo se pretenden desarrollar competencias a través de un proyecto práctico donde los estudiantes tendrán que resolver un problema real aplicado a ciudades inteligentes mediante internet de las cosas. Se propone una metodología de aprendizaje basada en proyectos (PBL) donde, a través de un proyecto, los estudiantes crearán y diseñarán su propio prototipo a una solución a un problema planteado, por ejemplo: gestionar automáticamente el alumbrado de una calle o habitación. Los estudiantes tendrán que razonar, analizar dicho reto y crear soluciones innovadoras basadas en STEAM al problema planteado. Los estudiantes diseñarán y construirán un prototipo real y tangible de la solución adoptada utilizando los sensores/actuadores y microcontroladores que ellos consideren. Después integrarán el prototipo diseñado en una pequeña maqueta (construida por los estudiantes como actividad inicial) que simulará una Smart City e interconectarán el prototipo creado con el resto de prototipos haciendo uso de Internet of Things. Finalmente, se realizarán foros de debate, donde participarán todos los estudiantes y moderarán los profesores, sobre las distintas soluciones aportadas con el objetivo de obtener retroalimentación de las propuestas desarrolladas para proponer nuevos retos, encontrar nuevas soluciones a otros problemas o para refinar las anteriores.This paper intends to develop competences through a practical project where students will have to solve a real problem applied to smart cities through the internet of things. A project-based learning methodology (PBL) where the students will create and design their own prototype to solve a given problem is proposed, for example: automatically manage the lighting of a street or room. Students will have to reason, analyze this challenge and create innovative solutions based on STEAM to the problem posed. Next, the students will design and build a real and tangible prototype of the solution adopted using the sensors/actuators and microcontrollers that they consider. They will integrate the prototype designed in a small model (built by the students as an initial activity) that simulates a Smart City and interconnect the prototype created with the rest of the prototypes using the Internet of Things. Finally, debate forums will be held, where all the students will participate and the professors will moderate, on the different solutions provided with the aim of obtaining feedback of the proposals

Towards a Circular Economy Development for Household Used Cooking Oil in Guayaquil: Quantification, Characterization, Modeling, and Geographical Mapping

This article belongs to the Special Issue Applications of GIS and Remote Sensing for Sustainable Development[Abstract] The objective of the present study was to quantify, geo-locate, model, and characterize domestic used cooking oil (dUCO) generation for the city of Guayaquil. For this reason, and as a prerequisite for the proper planning of municipal cooking oil waste management in the city, we carried out 14-day fieldwork involving 532 households from different parishes of Guayaquil, combined with a survey to acquire data on their demographic and socioeconomic statistics. The artisanal characterization was further executed to 40 subsamples of dUCO to determine the density, moisture, solids content, and the volatile-matter characteristics present. Additionally, the Geographic Information System (GIS) was used to map the used cooking oil generation hotspots for the city, adding the Geographical Position System (GPS) of each participating household during the data acquisition. Finally, a multiple-regression model was proposed to establish correlations between the dUCO generated and five independent variables, such as household size, socioeconomic group, tenure status, education level, and income. Results showed that the per capita daily dUCO-generation rate was found to be 4.30 g/day/c or 4.99 mL/day/c, with a density of 0.86 g/mL. Filterable solids represented 0.37% for the entire dUCO collected sample, while separable water and grease represented 1.58% and 0.014%, respectively. In addition, the percentage of the volatile matter was found to be 7.7% ± 2.1% of the filtered dUCO. Using GIS mapping, we found that the areas near tourism sites have a higher dUCO generation value, considering the household survey. Following the developed multiple-regression model developed, it was found that household size and the socioeconomic group have the maximum effect on generating used cooking oil

Digital Systems Laboratory for Visually Impaired Students

Comunicación presentada al 2nd ACM Workshop on Methods and Cases in Computing Education for the European Higher Education Area, celebrado en Barcelona el 22 de abril de 2009.This paper describes how the practical sessions of the Digital Systems Laboratory within the Computer Science Degree have been adapted to allow a visually impaired student to take part in the practical sessions. Regular students use a computer--aided design tool (OrCAD) for digital design in their practical assignments. This work shows how the use of special instrumentation allows visually impaired students to work with regular students in the same lab, where the CAD tool is installed. The teaching methodology and the obtained assessments are introduced here. Some specific practical materials have been designed and they are described in this work; the design of a special buzzer is also presente

Aplicación de PCA y técnicas bayesianas a la clasificación de píxeles basada en color

En este trabajo se propone un método para la clasificación de píxeles en base a su color. A partir de un conjunto de variables que caracterizan un píxel según su color se determinará cuáles de éstas son las más representativas y se realizará la clasificación propiamente dicha. Para ello nuestro método consta de dos fases: en la primera se aplica PCA para obtener el conjunto de variables características más informativas; en la segunda, dichas variables se utilizan como patrones de las clases de un clasificador bayesiano. El método se ilustra a través de varios experimentos

An Internet of Things and Fuzzy Markup Language Based Approach to Prevent the Risk of Falling Object Accidents in the Execution Phase of Construction Projects

The Internet of Things (IoT) paradigm is establishing itself as a technology to improve data acquisition and information management in the construction field. It is consolidating as an emerging technology in all phases of the life cycle of projects and specifically in the execution phase of a construction project. One of the fundamental tasks in this phase is related to Health and Safety Management since the accident rate in this sector is very high compared to other phases or even sectors. For example, one of the most critical risks is falling objects due to the peculiarities of the construction process. Therefore, the integration of both technology and safety expert knowledge in this task is a key issue including ubiquitous computing, real-time decision capacity and expert knowledge management from risks with imprecise data. Starting from this vision, the goal of this paper is to introduce an IoT infrastructure integrated with JFML, an open-source library for Fuzzy Logic Systems according to the IEEE Std 1855-2016, to support imprecise experts’ decision making in facing the risk of falling objects. The system advises the worker of the risk level of accidents in real-time employing a smart wristband. The proposed IoT infrastructure has been tested in three different scenarios involving habitual working situations and characterized by different levels of falling objects risk. As assessed by an expert panel, the proposed system shows suitable results.This research was funded by University of Naples Federico II through the Finanziamento della Ricerca di Ateneo (FRA) 2020 (CUP: E69C20000380005) and has been partially supported by the ”Programa de ayuda para Estancias Breves en Centros de Investigación de Calidad” of the University of Málaga and the research project BIA2016-79270-P, the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund-ERDF (Fondo Europeo de Desarrollo Regional-FEDER) under project PGC2018-096156-B-I00 Recuperación y Descripción de Imágenes mediante Lenguaje Natural usando Técnicas de Aprendizaje Profundo y Computación Flexible and the Andalusian Government under Grant P18-RT-2248