Project based learning on industrial informatics: applying IoT to urban garden

Copyright (c) 2018 IEEEThe fast evolution of technologies forces teachers to trade content off for self-learning. PBL is one of the best ways to promote self-learning and simultaneously boost motivation. In this paper, we present our experience introducing project-based learning in the last year subject. New Internet of Things (IoT) topic allows us to carry out complete projects, integrating different technologies and tools. Moreover, the selection of open-source and standard free technologies makes easy and cheap the access to hardware and software platforms used. We carefully have picked communication, data management, and programming tools that we think would be attractive to our students. They can start making fast prototyping with little initial skills and, at the same time, these are serious and popular tools widely used in the industry. In this paper, we report on the design of a project-based learning for our course and the impact this has on the student satisfaction and motivation. Surveys taught us that tuning the courses towards developing real projects on the field, has a large impact on acceptance, learning objectives achievements and motivation towards the course content.”I Plan Propio Integral de Docencia de la Universidad de Málaga” y Proyecto de Innovación Educativa PIE17/085, de la Universidad de Málaga. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Development of a Rooftop Collaborative Experimental Space through Experiential Learning Projects

The Solar, Water, Energy, and Thermal Laboratory (SWEAT Lab) is a rooftop experimental space at the University of Texas at Austin built by graduate and undergraduate students in the Cockrell School of Engineering. The project was funded by the Texas State Energy Conservation Office and the University’s Green Fee Grant, a competitive grant program funded by UT Austin tuition fees to support sustainability-related projects and initiatives on campus. The SWEAT Lab is an on-going experiential learning facility that enables engineering education by deploying energy and water-related projects. To date, the lab contains a full weather station tracking weather data, a rainwater harvesting system and rooftop garden. This project presented many opportunities for students to learn first hand about unique engineering challenges. The lab is located on the roof of the 10 story Engineering Teaching Center (ETC) building, so students had to design and build systems with constraints such as weight limitations and wind resistance. Students also gained experience working with building facilities and management for structural additions, power, and internet connection for instruments. With the Bird’s eye view of UT Austin campus, this unique laboratory offers a new perspective and dimension to applied student research projects at UT Austin.Cockrell School of Engineerin

Load flow studies on stand alone microgrid system in Ranau, Sabah

This paper presents the power flow or load flow analysis of Ranau microgrid, a standalone microgrid in the district of Ranau,West Coast Division of Sabah. Power flow for IEEE 9 bus also performed and analyzed. Power flow is define as an important tool involving numerical analysis applied to power system. Power flow uses simplified notation such as one line diagram and per-unit system focusing on voltages, voltage angles, real power and reactive power. To achieved that purpose, this research is done by analyzing the power flow analysis and calculation of all the elements in the microgrid such as generators, buses, loads, transformers, transmission lines using the Power Factory DIGSilent 14 software to calculate the power flow. After the analysis and calculations, the results were analysed and compared

STR: a student developed star tracker for the ESA-LED ESMO moon mission

In the frame of their engineering degree, ISAE’s students are developing a Star Tracker, with the aim of being the core attitude estimation equipment of the European Moon Student Orbiter. This development goes on since several years and is currently in phase B. We intend to start building an integrated breadboard for the end of the academic year. The STR is composed of several sub-systems: the optical and detection sub-system, the electronics, the mechanics and the software. The optical detection part is based on an in-house developed new generation of APS detectors. The optical train is made of several lenses enclosed in a titanium tube. The electronics includes a FPGA for the pre-processing of the image and a microcontroller in order to manage the high level functions of the instrument. The mechanical part includes the electronics box, as well as the sensor baffle. The design is optimized to minimize the thermo-elastic noise of the assembly. Embedded on ESMO platform, this Star Tracker will be able to compute the satellite‘s attitude, taking into account the specific requirements linked to a Moon mission (illumination, radiation requirements and baffle adaptation to lunar orbit). In order to validate the design, software end-to-end simulation will include a complete simulation of the STR in its lunar dynamic environment. Therefore, we are developing a simple orbital model for the mission (including potential dazzling by celestial bodies)

A Distributed Sensor Data Search Platform for Internet of Things Environments

Recently, the number of devices has grown increasingly and it is hoped that, between 2015 and 2016, 20 billion devices will be connected to the Internet and this market will move around 91.5 billion dollars. The Internet of Things (IoT) is composed of small sensors and actuators embedded in objects with Internet access and will play a key role in solving many challenges faced in today's society. However, the real capacity of IoT concepts is constrained as the current sensor networks usually do not exchange information with other sources. In this paper, we propose the Visual Search for Internet of Things (ViSIoT) platform to help technical and non-technical users to discover and use sensors as a service for different application purposes. As a proof of concept, a real case study is used to generate weather condition reports to support rheumatism patients. This case study was executed in a working prototype and a performance evaluation is presented.Comment: International Journal of Services Computing (ISSN 2330-4472) Vol. 4, No.1, January - March, 201

Optimization of star research algorithm for esmo star tracker

This paper explains in detail the design and the development of a software research star algorithm, embedded on a star tracker, by the ISAE/SUPAERO team. This research algorithm is inspired by musical techniques. This work will be carried out as part of the ESMO (European Student Moon Orbiter) project by different teams of students and professors from ISAE/SUPAERO (Institut Supe ́rieur de l’Ae ́ronautique et de l’Espace). Till today, the system engineering studies have been completed and the work that will be presented will concern the algorithmic and the embedded software development. The physical architecture of the sensor relies on APS 750 developed by the CIMI laboratory of ISAE/SUPAERO. First, a star research algorithm based on the image acquired in lost-in-space mode (one of the star tracker opera- tional modes) will be presented; it is inspired by techniques of musical recognition with the help of the correlation of digital signature (hash) with those stored in databases. The musical recognition principle is based on finger- printing, i.e. the extraction of points of interest in the studied signal. In the musical context, the signal spectrogram is used to identify these points. Applying this technique in image processing domain requires an equivalent tool to spectrogram. Those points of interest create a hash and are used to efficiently search within the database pre- viously sorted in order to be compared. The main goals of this research algorithm are to minimise the number of steps in the computations in order to deliver information at a higher frequency and to increase the computation robustness against the different possible disturbances