Leading Undergraduate Students to Big Data Generation

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students handson abilities on Big Data and their critical thinking abilities. The authors used novel image based rendering algorithm with user intervention to generate realistic 3D virtual world. The learning outcomes are significant

Integration of a wireless sensor network project for introductory circuits and systems teaching

This paper presents an integration of a wireless sensor network design project in an introductory course about circuits and systems. In the project, students will design a wireless sensor network that constitutes of sensors, for a creative surveillance application. Through a versatile project vehicle, project-oriented learning modules, a comprehensive assessment strategy and public learning communities, students can learn contemporary concepts of circuits and systems from the system perspective, as well as develop ability to design a basic electronic system. © 2013 IEEE.published_or_final_versio

Systems for pervasive electronics and interfaces

Energy Harvesting Active Networked Tags (EnHANTs) are a new type of wireless device in the domain between RFIDs and sensor networks. Future EnHANTs will be small, flexible, and self-powered devices that can be attached to everyday objects that are traditionally not networked to enable "Internet of Things" applications. This work describes the design and development of the EnHANT prototypes and testbed. The current prototypes use thin-film photovoltaics optimized for indoor light harvesting, form multihop networks using ultra-low-power Ultra-Wideband Impulse Radio (UWB-IR) transceivers, and implement energy harvesting adaptive networking protocols. The current testbed enables the evaluation of different algorithms by exposing individual prototypes to repeatable light conditions based on real-world irradiance data. New approaches to characterizing the energy available to energy harvesting devices were explored. A mobile data-logger was used to record the intensity of ambient light, determine the light source, and record the acceleration from motion during different real world activities. These traces were used to model the behavior of photovoltaic and inertial energy harvesters in real world deployments and can be replayed in the EnHANTs testbed. In addition, new techniques to evaluate the efficiency of different photovoltaic technologies under indoor illumination were developed. A proof-of-concept system was built to characterize photovoltaics under a standardized set of conditions in which the radiant intensity and spectral composition of the light source were systematically varied. Techniques to structure student research projects within the EnHANTs project were developed. Project-based learning approaches were implemented to engage students using real-world system development constraints. A survey of the students showed that this approach is an effective method for developing technical, professional, and soft skills. Open source hardware was also applied to EnHANTs project and extended into other domains. A laboratory-based class in flat panel display technology was developed. The course introduces fundamental concepts of display systems and reinforces these concepts through the fabrication of three display devices. A lab kit platform was developed to enable remote students to use low-cost, course specific hardware to complete the lab exercises remotely. This platform was also applied to external projects targeted at non-university students. A workshop was developed to teach artists, designers, and hobbyists how to design and build custom user interfaces using thin-film electronics and rapid prototyping tools. Surveys of the students and workshop participants showed that this platform is an effective teaching tool and can be easily adapted and expanded

Developing a Wireless Sensor Network Programming Language Application Guide Using Memsic Devices and LabVIEW

The principal objective of this project is to develop a wireless sensor network (WSN) programming language application guide for junior and senior undergraduate students in College of Technology, Architecture and Applied Engineering in Bowling Green State University. Memsic device, MoteWorks and LabVIEW software are used to conduct experiments in developing WSN applications after both software and hardware platform are verified to be usable with experimental and statistical analysis. The guide is divided into six chapters including both theoretical knowledge and practical experiments in WSN area. Programs, both in nesC language and LabVIEW are improved from previous work, tested to run successfully and noted in detail

The Internet of Things: the future or the end of mechatronics.

The advent and increasing implementation of user configured and user oriented systems structured around the use of cloud configured information and the Internet of Things is presenting a new range and class of challenges to the underlying concepts of integration and transfer of functionality around which mechatronics is structured. It is suggested that the ways in which system designers and educators in particular respond to and manage these changes and challenges is going to have a significant impact on the way in which both the Internet of Things and mechatronics develop over time. The paper places the relationship between the Internet of Things and mechatronics into perspective and considers the issues and challenges facing systems designers and implementers in relation to managing the dynamics of the changes required

Teaching Big Data by Three Levels of Projects

Big Data is a new topic and it is very hot nowadays. However, it is difficult to teach Big Data effectively by regular lecture. In this paper, we present a unique way to teach students Big Data by developing three levels of projects from easy to difficult. The three levels projects are initializing project, designing project, and comprehensive projects. They are developed to involve students in Big Data, train students\u27 skills to analyze concrete problems of Big Data, and develop students\u27 creative abilities and their abilities to solve real setting problems

Educating the Internet-of-Things generation

As highlighted by the articles in this special issue, the concept of the Internet of Things is becoming increasingly important and understanding both the technical underpinning and wider societal impacts of the Internet of Things (IoT) will be crucial for digital citizens of the future. Building on extensive experience in delivering large-scale distance learning, The Open University has redesigned its introductory computer science curriculum to place the Internet of Things at the centre of students’ experience, in a course called My Digital Life. In this article we present the design of this module, including a learning infrastructure that allows complete novices to experiment with, and learn about, Internet of Things technologies. We also share our experience of having almost 2000 students participate in the first presentation of the course, engaging in a range of activities that include collaborative and collective programming of real-world sensing applications