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

Cloud Chaser: Real Time Deep Learning Computer Vision on Low Computing Power Devices

Internet of Things(IoT) devices, mobile phones, and robotic systems are often denied the power of deep learning algorithms due to their limited computing power. However, to provide time-critical services such as emergency response, home assistance, surveillance, etc, these devices often need real-time analysis of their camera data. This paper strives to offer a viable approach to integrate high-performance deep learning-based computer vision algorithms with low-resource and low-power devices by leveraging the computing power of the cloud. By offloading the computation work to the cloud, no dedicated hardware is needed to enable deep neural networks on existing low computing power devices. A Raspberry Pi based robot, Cloud Chaser, is built to demonstrate the power of using cloud computing to perform real-time vision tasks. Furthermore, to reduce latency and improve real-time performance, compression algorithms are proposed and evaluated for streaming real-time video frames to the cloud.Comment: Accepted to The 11th International Conference on Machine Vision (ICMV 2018). Project site: https://zhengyiluo.github.io/projects/cloudchaser

IntelliWay: Connecting Bicycles to the V2V Network

The IntelliWay device aims to assist cyclists to avoid accidents with motorized vehicles. The project summarizes an innovative device that could provide safer travel for cyclists. Related findings on similar solutions such as bike traffic in heavily populated areas, highway infrastructure, Inter-Car-Communication Systems and the art of merging, have been documented. The project will cover approaches to the initial design and the system specifications for the device with future goals and detailed tasks and schedules

An Experimental Framework for 5G Wireless System Integration into Industry 4.0 Applications

The fourth industrial revolution, or Industry 4.0 (I4.0), makes use of wireless technologies together with other industrial Internet-of-Things (IIoT) technologies, cyber–physical systems (CPS), and edge computing to enable the optimization and the faster re-configuration of industrial production processes. As I4.0 deployments are ramping up, the practical integration of 5G wireless systems with existing industrial applications is being explored in both Industry and Academia, in order to find optimized strategies and to develop guidelines oriented towards ensuring the success of the industrial wireless digitalization process. This paper explores the challenges arisen from such integration between industrial systems and 5G wireless, and presents a framework applicable to achieve a structured and successful integration. The paper aims at describing the different aspects of the framework such as the application operational flow and its associated tools, developed based on analytical and experimental applied research methodologies. The applicability of the framework is illustrated by addressing the integration of 5G technology into a specific industrial use case: the control of autonomous mobile robots. The results indicate that 5G technology can be used for reliable fleet management control of autonomous mobile robots in industrial scenarios, and that 5G can support the migration of the on-board path planning intelligence to the edge-cloud

Portable Fog Gateways for Resilient Sensors Data Aggregation in Internet-less Environment

Fog computing is gaining attention due to the potential of aggregating and processing time-sensitive data at the nearby intelligent gateways. It reduces the latency of sensors data aggregation and response time therefore, improve real-time action which is beneficial in environmental monitoring and early warning systems. However, deploying edge computing in Internet-less environment seems unpractical and the mobility of gateways is less focused in current literature. In this paper, we present a practical design of a portable gateways scheme for sensors data aggregation and processing in Internet-less environment. The proposed gateways can locate their geographical locations which can be automatically converted into location names at the central gateway. The proposed portable Fog Gateways are developed by using open-source hardware and integrated with Cloud database for data storage. Data processing techniques such as data parsing and Reverse Geocoding are conducted for reliable data transmission by using GSM/GPRS technology and geographical location name detection respectively. Finally, a case study has been conducted to evaluate the feasibility of our proposed Fog Gateways scheme in real-time application

Autonomous Search and Rescue Helicopter System Design

The objective of this project is to design and implement an autonomous search-and-rescue drone system capable of operating on targets positioned within a 30 ft. radius. Targets are located through heat signature, after which the drone performs a controlled approach to retrieve the rescuee and return to the launch point. The Pixhawk 4 autopilot is utilized to run autonomous missions, an IR camera to identify the target through OpenCV, and a winch system to pull the victim to safety. The flight director is designed in MATLAB/Simulink to help guide the drone to the precise location of the target. Simulations of the drone are run using jMAVSim to test software-in-the-loop implementations. At the project’s conclusion, several requirements have been fulfilled, while others remain incomplete due to unforeseen obstacles. Although the drone hardware has been assembled and image detection and UAV communication capabilities on the offboard computer are fully functional, the Simulink flight director component of the rescue loop was not completed and test flights of the drone were unsuccessful. The team faced some challenges, such as global chip shortage, limited budget, time constraints, and weight capacity