Smart Glasses for the Visually Impaired People

Engineering solutions have involved in everyone’s life, most importantly are those aiming to help people with disabilities, however, the modern assistance devices with their current prices are not meeting the requirements of the market. This project is mainly focusing on people with visual impairments and more specifically their education life. It is presenting a concept of smart glasses to provide assistance in multiple tasks represented as modes to be chosen by the user. To prove the concept, this project implements only one mode which is reading using text detection techniques. Taking into consideration the cost, this project is using the single board computer raspberry pi 2 as the heart of the processing and the raspberry pi camera for image capturing and video recording. The video taken is processed using MATLAB, and the description of the live scenes for the text recognition mode or any other future implemented modes will be provided to the user in an audio format. Finally the results of this project show the design of the smart glasses prototype

OPEB: Open Physical Environment Benchmark for Artificial Intelligence

Artificial Intelligence methods to solve continuous- control tasks have made significant progress in recent years. However, these algorithms have important limitations and still need significant improvement to be used in industry and real- world applications. This means that this area is still in an active research phase. To involve a large number of research groups, standard benchmarks are needed to evaluate and compare proposed algorithms. In this paper, we propose a physical environment benchmark framework to facilitate collaborative research in this area by enabling different research groups to integrate their designed benchmarks in a unified cloud-based repository and also share their actual implemented benchmarks via the cloud. We demonstrate the proposed framework using an actual implementation of the classical mountain-car example and present the results obtained using a Reinforcement Learning algorithm.Comment: Accepted in 3rd IEEE International Forum on Research and Technologies for Society and Industry 201

The Glasgow raspberry pi cloud: a scale model for cloud computing infrastructures

Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud Computing research and educational environment

Cyber security investigation for Raspberry Pi devices

Big Data on Cloud application is growing rapidly. When the cloud is attacked, the investigation relies on digital forensics evidence. This paper proposed the data collection via Raspberry Pi devices, in a healthcare situation. The significance of this work is that could be expanded into a digital device array that takes big data security issues into account. There are many potential impacts in health area. The field of Digital Forensics Science has been tagged as a reactive science by some who believe research and study in the field often arise as a result of the need to respond to event which brought about the needs for investigation; this work was carried as a proactive research that will add knowledge to the field of Digital Forensic Science. The Raspberry Pi is a cost-effective, pocket sized computer that has gained global recognition since its development in 2008; with the wide spread usage of the device for different computing purposes. Raspberry Pi can potentially be a cyber security device, which can relate with forensics investigation in the near future. This work has used a systematic approach to study the structure and operation of the device and has established security issues that the widespread usage of the device can pose, such as health or smart city. Furthermore, its evidential information applied in security will be useful in the event that the device becomes a subject of digital forensic investigation in the foreseeable future. In healthcare system, PII (personal identifiable information) is a very important issue. When Raspberry Pi plays a processor role, its security is vital; consequently, digital forensics investigation on the Raspberry Pies becomes necessary

SISTEM MONITORING SUHU HEWAN MARMOT MENGGUNAKAN RASPBERRY PI BERBASIS IoT

ABSTRAK Farida Nurhasanah, Sistem Monitoring Suhu Hewan Marmot Menggunakan Raspberry Pi Berbasis IoT. Skripsi. Jakarta: Program Studi Pendidikan Teknik Elektronika, Fakultas Teknik, Universitas Negeri Jakarta, 2020. Dosen Pembimbing, Dr. Muhammad Yusro, MT dan Taryudi, Ph.D. Tujuan penelitian ini adalah merancang dan mengembangkan sistem pendeteksi suhu tubuh pada hewan dengan menggunakan kamera berbasis IoT untuk memudahkan pemilik hewan memantau kondisi hewan yang dimilikinya.Penelitian ini dilakukan dengan menggunakan metode rekayasa teknik dengan tahapan Research and Development (R&D). Sistem yang dibuat, direalisasikan menggunakan 2 subsistem yaitu : (1) Kamera NoIR AMG8833, (2) (3) Raspberry Pi 3 Model B+. Hasil pengukuran pada alat dibuat dan diolah menggunakan image processing.Hasil dari penelitian menunjukkan bahwa kinerja sistem alat berjalan dengan baik dapat mengukur suhu dari minimal 25oC sampai dengan 50oC. Jika dibandingkan dengan alat konvensional alat ini dapat mengukur suhu tubuh hewan marmot dengan persentasi error 2,85%. Kata-Kata Kunci : Suhu Marmot, Kamera Thermal, Raspberry Pi, IoT. ABSTRACT Farida Nurhasanah, Marmot Animal Temperature Monitoring System Using Raspberry Pi Based on IoT. Minithesis. Jakarta, Major Education of Electronics Engineering, Faculty of Engineering, Universitas Negeri Jakarta, 2020. Supervisor are Dr. Muhammad Yusro, MT dan Taryudi, Ph.D. The purpose of this study is to design and develop a body temperature detection system in animals using an IoT-based camera to make it easy for animal owners to monitor the condition of the animals they have. This research was conducted using engineering methods with stages of Research and Development (R&D). The system is created, realized using 2 subsystems, that is: (1) Kamera NoIR AMG8833, (2) (3) Raspberry Pi 3 Model B+. The measurement results on the device are made and processed using image processing. The results of the study showed that the performance of the tool system was running properly could measure temperatures from a minimum of 25oC to 40oC . When compared with conventional tools, this tool can measure the body temperature of guinea pigs with an error percentage of 2.85%. Keywords: Marmot Temperature, Thermal Camera, Raspberry Pi, IoT