AUTOMATIC ACCIDENT DETECTION AND RESCUE SYSTEM

The rapid growth of technology and infrastructure has made our lives easier. The advent of technology has also increased the traffic hazards and the road accidents take place frequently which causes huge loss of life and property because of the poor emergency facilities. Our project will provide an optimum solution to this draw back. According to this project when a vehicle meets with an accident immediately Vibration sensor will detect the signal and sends it to Microcontroller. Microcontroller find the location coordinates of accident spot using GPS and sends the alert message including geographic allocation coordinates through the GSM Module to ambulance unit. So the rescue team in the ambulance can immediately trace the location by putting geographical location coordinates in Google earth application or any other Geographic location finder application. After conforming the location of accident spot the ambulance unit will starts its rescue operation. This system also controls the traffic signals in the path of ambulance and helps ambulance to reach hospital in minimum time

Remote Healthcare Monitoring System Using IoT SaaS

With an improvement in technology and miniaturization of sensors, there have been attempts to utilize the new technology in various areas to improve the quality of human life. One main area of research that has seen an adoption of the technology is the healthcare sector. The people in need of healthcare services find it very expensive this is particularlytrue in developing countries. As a result, this project is an attempt to solve a healthcare problem currently society is facing. The main objective of the project was to design aremote healthcare system. It’s comprised of three main parts. The first part being, detection of patient’s vitals using sensors, second for sending data to cloud storage and the last part was providing the detected data for remote viewing. Remote viewing of the data enables a doctor or guardian to monitor a patient’s health progress away from hospital premises. The Internet of Things (IoT) concepts have been widely used to interconnect the available medical resources and offer smart, reliable, and effective healthcare service to the patients. Health monitoring for active and assisted living is one of the paradigms that can use the IoT advantages to improve the patient’s lifestyle. In this project, I have presented an IoT architecture customized for healthcare applications. The aim of the project was to come up with a Remote Health Monitoring System that can be made with locally available sensors with a view to making it affordable if it were to be mass produced. Hence the proposed architecture collects the sensor data through Arduino microcontroller and relays it to the cloud where it is processed and analyzed for remote viewing. Feedback actions based on the analyzed data can be sent back to the doctor or guardian through Email and/or SMS alerts in case of any emergency

An innovative IoT service for medical diagnosis

Due to the misdiagnose of diseases that increased recently in a scarily manner, many researchers devoted their efforts and deployed technologies to improve the medical diagnosis process and reducing the resulted risk. Accordingly, this paper proposed architecture of a cyber-medicine service for medical diagnosis, based internet of things (IoT) and cloud infrastructure (IaaS). This service offers a shared environment for medical data, and extracted knowledge and findings between patients and doctors in an interactive, secured, elastic and reliable way. It predicts the medical diagnosis and provides an appropriate treatment for the given symptoms and medical conditions based on multiple classifiers to assure high accuracy. Moreover, it entails different functionalities such as on-demand searching for scientific papers and diseases description for unrecognized combination of symptoms using web crawler to enrich the results. Where such searching results from crawler, are processed, analyzed and added to the resident knowledge base (KB) to achieve adaptability and subsidize the service predictive ability

El estado del arte: Salud inteligente y el internet de las cosas

El Internet de las cosas (IoT) es la nueva tendencia de dispositivos en el mercado. Esta tecnología está siendo desarrollada por múltiples fabricantes de diversas partes del mundo para solucionar problemas específicos del día a día de las personas. Sin embargo, en la actualidad se están dando muchos casos de fallas de seguridad en dispositivos IoT, en este caso en hospitales. En este escrito también se describe el IoT como un complemento al sector salud haciendo referencia a las tecnologías creadas e implementadas por distintos fabricantes. Se presentan también los distintos métodos de seguridad que los fabricantes han implementado en sus soluciones y sus productos, desde diseños de topologías alámbricas e inalámbricas, hasta seguridad perimetral estricta de capa 2 y capa 3, las cuales trabajan en conjunto con la programación segura y recomendaciones para que el usuario final realice el uso adecuado del mismo. Al final del escrito se presenta la tecnología WBAN y los riesgos que conlleva junto con el IoT si no se asegura adecuadamente, ya que podría ser crítico y pondría en riesgo la vida de los pacientes. El objetivo es implementar en nuestro sistema IoT una capa extra de seguridad informática sin depender que el fabricante la haya embebido en su producto. Dicha capa dificulta que el atacante pueda manipular nuestros equipos a su conveniencia o que pueda explotar una falla conocida en un dispositivo que pueda perjudicar la vida, salud e integridad del paciente

High-efficiency Urban-traffic Management in Context-aware Computing and 5G Communication

With the increasing number of vehicle and traffic jams, urban-traffic management is becoming a serious issue. In this article, we propose novel four-tier architecture for urban-traffic management with the convergence of vehicle ad hoc networks (VANETs), 5G wireless network, software-defined network (SDN), and mobile-edge computing (MEC) technologies. The proposed architecture provides better communication and rapider responsive speed in a more distributed and dynamic manner. The practical case of rapid accident rescue can significantly cut down the time for rescue. Key technologies with respect to vehicle localization, data pre-fetching, traffic lights control, and traffic prediction are also discussed. Obviously, the novel architecture shows noteworthy potential for alleviating the traffic congestion and improving the efficiency of urban-traffic management

Organisational design practices for achieving environmental sustainability performance: a best-worst method

This study illustrates a ranking of organisational design practices for achieving environmental sustainability performance. Organisations can achieve environmental sustainability with production processes and operations that aim to reduce raw material and energy usage. Thus, organisations may adopt novel technologies and change work practices to achieve such outcomes. To accommo- date such changes, organisations use some organisational design practices. Since there is a lack of studies that summarises such practices illustrating the most im- portant to the least important, I decided to conduct a best-worst method. This method allows a ranking of several criteria that, in the study, are represented by organisational design practices, which are retrieved from the literature. The study results show that the development of the R&D function is the best organisational design practice to achieve environmental sustainability performance

Deep Learning-aided Brain Tumor Detection: An Initial ‎Experience based Cloud Framework ‎

Lately, the uncertainty of diagnosing diseases increased and spread due to the huge intertwined and ambiguity of symptoms, that leads to overwhelming and hindering the reliability of the diagnosis ‎process. Since tumor detection from ‎MRI scans depends mainly on the specialist experience, ‎misdetection will result an inaccurate curing that might cause ‎critical harm consequent results. In this paper, detection service for brain tumors is introduced as ‎an aiding function for both patients and specialist. The ‎paper focuses on automatic MRI brain tumor detection under a cloud based framework for multi-medical diagnosed services. The proposed CNN-aided deep architecture contains two phases: the features extraction phase followed by a detection phase. The contour ‎detection and binary segmentation were applied to extract the region ‎of interest and reduce the unnecessary information before injecting the data into the model for training. The brain tumor ‎data was obtained from Kaggle datasets, it contains 2062 cases, ‎‎1083 tumorous and 979 non-tumorous after preprocessing and ‎augmentation phases. The training and validation phases have been ‎done using different images’ sizes varied between (16, 16) to ‎‎ (128,128). The experimental results show 97.3% for detection ‎accuracy, 96.9% for Sensitivity, and 96.1% specificity. Moreover, ‎using small filters with such type of images ensures better and faster ‎performance with more deep learning.

A Cloud Mobile-Based Information Retrieval and Optimal Route Service Delivery System for Aiding the Treatment of Diabetic Patients in Nigeria

Diabetes is considered as one of the most incurable diseases in the world. Studies have shown that at least fourteen million, four hundred and six thousand Nigerians are currently living with the incurable disease. Several researchers have proposed the use of mobile technology to aid diabetes treatment, but challenges such as time taken for physicians to attend to patients due to unavailable Information and problems associated with location of hospitals are recurrent. This research approached these challenges by developing a cloud mobile-based Information retrieval and optimal route service delivery system for aiding the treatment of diabetic patients in Nigeria