Integrated Smart Home Model

Author(s):  
Nurshahrily Idura Ramli ◽  
Mohd Izani Mohamed Rawi ◽  
Fatin Nur Nabila Rebuan

Today, in the realm of Industry 4.0, vastly diverse Internet of Things (IoT) technology are integrated everywhere, not to mention included in academic programs in schools and universities. Domain ratio of the final year projects in Universiti Teknologi Mara exposes a staggering hype in IoT as compared to other domains despite not having IoT included in any of the courses. Meanwhile, to fulfill the needs of the student in exploring this technology, an integrated IoT learning platform is developed. It integrates an IoT smart home model and a web-based interface as a learning platform to inspire hands-on learning for the students. The raspberry pi, motion sensor, analog gas sensor, atmospheric sensor, ultrasonic proximity sensor, and rain detector sensor are integrated together in a Lego-built smart home model where its connectivity and readings are displayed in a simple web interface to enable and inspire learning. A manual to set up the entire model is also prepared as a guide for students to set up and further explore the functionalities and operabilities of “things”.

2016 ◽  
Vol 861 ◽  
pp. 556-563 ◽  
Author(s):  
Matthias Schuss ◽  
Stefan Glawischnig ◽  
Ardeshir Mahdavi

Efforts toward optimized building management and operation require monitoring data from multiple sources. Experiences from previous research projects underline the need for an easily adaptable, low-cost, and easy to set up monitoring infrastructure that could provide data for modeling and performance evaluation. The increasing availability of small and powerful development boards (e.g. Raspberry Pi BeagleBoard or Arduino) facilitates the implementation of a cost-efficient infrastructure for data collection and building monitoring. For the purpose of the present contribution, the Arduino Yún was used to create a data logger that obtains data from wireless sensors, stores it locally, and syncs it with a data repository. Toward this end, we have developed a web-based user interface that enables the user to evaluate various aspects of the monitored building's performance. The communication between the software components is implemented via RESTful interfaces and enables the user to integrate also other data sources such as web services. The paper includes an actual implementation of the above approach. Thereby, we illustrate how the constitutive system components can be integrated in terms of a versatile monitoring system with multiple utilities in terms of building performance assessment and building diagnostics.


2020 ◽  
Vol 245 ◽  
pp. 05040
Author(s):  
Max Beer ◽  
Niclas Eich ◽  
Martin Erdmann ◽  
Peter Fackeldey ◽  
Benjamin Fischer ◽  
...  

The VISPA (VISual Physics Analysis) project provides a streamlined work environment for physics analyses and hands-on teaching experiences with a focus on deep learning. VISPA has already been successfully used in HEP analyses and teaching and is now being further developed into an interactive deep learning platform. One specific example is to meet knowledge sharing needs in deep learning by combining paper, code and data at a central place. Additionally the possibility to run it directly from the web browser is a key feature of this development. Any SSH reachable resource can be accessed via the VISPA web interface. This enables a flexible and experiment agnostic computing experience. The user interface is based on JupyterLab and is extended with analysis specific tools, such as a parametric file browser and TensorBoard. Our VISPA instance is backed by extensive GPU resources and a rich software environment. We present the current status of the VISPA project and its upcoming new features.


Author(s):  
Huimin Han

This paper attempts to solve the following problems of traditional Internet Eng-lish learning websites: the emphasis on the teaching process over the timely feed-back of the students, the bottleneck on the autonomous learning ability of the stu-dents, and the delay in the update of relevant resources. For this purpose, the au-thor established a web-based English autonomous learning platform. Specifically, the conceptual model was analysed by the object-oriented technology, the brows-er/server (B/S) architecture was set up to send data to the ADO.NET-based backend database, and displayed as webpages. The research results show that the design and implementation of the proposed system offers a preliminary solution to the lack of collaborative communication in traditional webpage learning, and widens the range of resource sharing. The system is in line with the English learners’ demand for and interests in Internet learning, and arouses the students’ interests and enthusiasm of English learning.


Author(s):  
Stephanie Elaine Burnett

Online courses in horticulture increase the breadth of students who may be able to enroll. However, it is challenging to create hands-on learning experiences in online classes that are valuable for student learning. In an online introduction to horticulture class at the University of Maine, we created a hands-on project that is appropriate for students to work on independently at home. Students built an environmental monitoring system using a relatively inexpensive Raspberry Pi microcomputer and sensors for monitoring environmental factors that impact plant growth with a particular focus on monitoring temperature and humidity. They monitored the growing environment in their homes while growing house plants and used the information from their environmental monitoring system to determine whether their home environment was suitable for growing plants. Students were asked to use a pre-existing computer program in the Python language to monitor the environment. They also learned about how components of the code function and changed some simple parts of the code. A majority of students working on this project felt moderately confident, somewhat more confident, or very confident about their ability to use a Raspberry Pi microcomputer in the future. This project provides students with valuable hands-on experience in building environmental monitoring systems and provides them with a deeper understanding of the impact of the environment on plant growth.


2009 ◽  
Vol 13 (1) ◽  
Author(s):  
Kelly Fadel ◽  
David Olsen ◽  
Karina Hauser

The growing popularity of Internet-enabled commerce has produced increased demand for Information Technology (IT) professionals who are skilled in the development and management of data-driven, Web-based business applications. Many academic programs in information systems offer courses on relational database design and management, as well as courses on Web development using technologies such as PHP or Microsofts ASP.NET. However, such courses typically contain independent content, which tends to leave students with a fragmented understanding of how these technologies (i.e. the Web and relational databases) interact. In this paper, we present integrated instructional modules for teaching best practices in connecting advanced Web applications with a relational database backend. The objective of these modules is to provide students with a seamless context for developing both a relational database and a Web interface supporting database transactions.


2016 ◽  
Author(s):  
René A. Zelaya ◽  
Aaron K. Wong ◽  
Alex T. Frase ◽  
Marylyn D. Ritchie ◽  
Casey S. Greene

AbstractBackgroundThe adoption of new bioinformatics webservers provides biological researchers with new analytical opportunities but also raises workflow challenges. These challenges include sharing collections of genes with collaborators, translating gene identifiers to the most appropriate nomenclature for each server, tracking these collections across multiple analysis tools and webservers, and maintaining effective records of the genes used in each analysis.DescriptionIn this paper, we present the Tribe webserver (available at https://tribe.greenelab.com), which addresses these challenges in order to make multi-server workflows seamless and reproducible. This allows users to create analysis pipelines that use their own sets of genes in combinations of specialized data mining webservers and tools while seamlessly maintaining gene set version control. Tribe’s web interface facilitates collaborative editing: users can share with collaborators, who can then view, download, and edit these collections. Tribe’s fully-featured API allows users to interact with Tribe programmatically if desired. Tribe implements the OAuth 2.0 standard as well as gene identifier mapping, which facilitates its integration into existing servers. Access to Tribe’s resources is facilitated by an easy-to-install Python application called tribe-client. We provide Tribe and tribe-client under a permissive open-source license to encourage others to download the source code and set up a local instance or to extend its capabilities.ConclusionsThe Tribe webserver addresses challenges that have made reproducible multi-webserver workflows difficult to implement until now. It is open source, has a user-friendly web interface, and provides a means for researchers to perform reproducible gene set based analyses seamlessly across webservers and command line tools.


Author(s):  
Tate Ning. Cao ◽  
Wayne Chang ◽  
Carlos Bazan ◽  
Kush Bubbar

The spread of COVID-19 has significantly disrupted the educational landscape since March 2020.Instructors at higher education institutions had to quickly transition to an online environment for remote delivery of their academic programs. Even though academic programs are relatively easy to adapt for remote delivery as compared to other industries, educators were still tasked with redesigning their courses to guarantee the quality of education delivered to their students.  This challenge is particularly true with engineering entrepreneurship educators since their course structures heavily focus on developing intangibles such as an entrepreneurial mindset and team collaboration through immersion into hands-on learning experiences. To create this experiential learning environment, engineering entrepreneurship educators have, in general, relied uponface-to-face interactions with students. Little has been published in the existing literature to report the challenges, strategies, and innovations that can help transition effectively and deliver such academic programs remotely. In this paper, the authors from four major Canadian higher education institutions report our experience from ‘trial-byfire’ mode to redesign and deliver various courses for remote learning. This paper is by no means presenting validated “best practices” but aims to trigger discussions surrounding tools available to educators considering such a transition. We hope that this paper will provide insights and strategies for our colleagues to employ in their future course design and delivery. We also hope to invite a conversation to learn more about our colleagues’ experiences and explore opportunities to identify and validate approaches for effectively teaching engineering entrepreneurship in a remote learning environment.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Alexandros Gazis ◽  
Eleftheria Katsiri

Computer scientists and researchers have focused their efforts on advancing from traditional computing techniques to the use of “Industry 4.0”. Specifically, this term includes breakthroughs in numerous fields, including manufacturing, Artificial Intelligence, machine learning and data science. Additionally, emphasis is placed on the so-called “Internet of Things”, i.e. the development of interconnected devices capable of communicating and processing information, mainly from sensory networks. This article presents electronic devices used for home automation. Specifically, it presents different types of residential sensors which can transform a traditional house to a “smart home”. Furthermore, it reviews their possible uses, such as for ventilation, security and temperature monitoring. Lastly, for each of the sensors, the article recommends low-cost sensory devices to set up affordable home automation projects, such as an Arduino and a Raspberry Pi.


Author(s):  
Norman Gwangwava

Design thinking is a human-centered, team-based, creative, and iterative process for problem-solving. The process focuses on the end-user and applies empathy skills to gain an understanding of the problem. Unlike other design methodologies, design thinking dwells much on the most prominent user of the design solution. Industry 4.0 is characterized by fast-changing technology, which requires quick time-to-market solutions. Industry 4.0 applications involve more end-user interaction. In order to design products, applications, and systems that end-users will be comfortable to use, designers should engage users throughout the design process. Design thinking brings together key parameters for achieving innovative user-centered design solutions. In addition to bringing together designers to work as multidisciplinary teams, the process factors in a creative environment under which the teams work. The article presents a case study for hands-on learning of design thinking where groups of students were engaged in solving pressing problems encountered by skilled craftsmen in the digital era.


2019 ◽  
Vol 8 (3) ◽  
pp. 1108-1116
Author(s):  
Siti Noorjannah Ibrahim ◽  
A. H. Hasan Basri ◽  
Ani Liza Asnawi

With the advancement of wireless technology, our dependency on smart system has increases to a higher level than before. Without doubt, integration between different technologies becomes inevitable in order create affordable surveillance system. This paper presents the development of with web-based surveillance system with a dedicated Android-based mobile application using a Raspberry Pi and its supporting components i.e., Pi-Camera, PIR motion sensor, Ultrasonic sensor, web-based mobile application. The designed system also utilizes Node-Red development tools as the platform to integrate all components of the system, MQTT as the communication protocol for data acquisition and ThingSpeak as the middleware. The proposed system can be implemented over the internet using any computer and mobile devices, at anywhere and anytime. The system can automatically stream live video viewed from the Android mobile application and the Raspberry Pi device can send an alert notification to users via email and SMS. The system can be one possible features in smart home system and is considered as an affordable solution, customizable and easy to implement in comparison with other commercial surveillance system products such as CCTV or IP Camera.


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