The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure

System dynamics : Applications in management and policy 1

We turn on the lights in our house from a desk in an office miles away. Our refrigerator alerts us to buy milk on the way home. A package of cookies on the supermarket shelf suggests that we buy it, based on past purchases. The cookies themselves are on the shelf because of a "smart" supply chain. When we get home, the thermostat has already adjusted the temperature so that it's toasty or bracing, whichever we prefer. This is the Internet of Things -- a networked world of connected devices, objects, and people. In this book, Samuel Greengard offers a guided tour through this emerging world and how it will change the way we live and work. Greengard explains that the Internet of Things (IoT) is still in its early stages. Smart phones, cloud computing, RFID (radio-frequency identification) technology, sensors, and miniaturization are converging to make possible a new generation of embedded and immersive technology. Greengard traces the origins of the IoT from the early days of personal computers and the Internet and examines how it creates the conceptual and practical framework for a connected world. He explores the industrial Internet and machine-to-machine communication, the basis for smart manufacturing and end-to-end supply chain visibility; the growing array of smart consumer devices and services -- from Fitbit fitness wristbands to mobile apps for banking; the practical and technical challenges of building the IoT; and the risks of a connected world, including a widening digital divide and threats to privacy and security. Finally, he considers the long-term impact of the IoT on society, narrating an eye-opening "Day in the Life" of IoT connections circa 2025.

The Internet of Things

Home automation systems have attracted considerable attention with the advancement of communications technology. A smart home (SH) is an Internet of Things (IoT) application that utilizes the Internet to monitor and control appliances using a home automation system. Lack of IoT technology usage, unfriendly user interface, limited wireless transmission range, and high costs are the limitations of existing home automation systems. Therefore, this study presents a cost-effective and hybrid (local and remote) IoT-based home automation system with a user-friendly interface for smartphones and laptops. A prototype called IoT@HoMe is developed with an algorithm to enable the monitoring of home conditions and automate the control of home appliances over the Internet anytime and anywhere. This system utilizes a node microcontroller unit (NodeMCU) as a Wi-Fi-based gateway to connect different sensors and updates their data to Adafruit IO cloud server. The collected data from several sensors (radio-frequency identification, ultrasonic, temperature, humidity, gas, and motion sensors) can be accessed via If This Then That (IFTTT) on users' devices (smartphones and/or laptops) over the Internet regardless of their location. A set of relays is used to connect the NodeMCU to homes under controlled appliances. The designed system is structured in a portable manner as a control box that can be attached for monitoring and controlling a real house. The proposed IoT-based system for home automation can easily and efficiently control appliances over the Internet and support home safety with autonomous operation. IoT@HoMe is a low cost and reliable automation system that reduces energy consumption and can notably provide convenience, safety, and security for SH residents.

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Design and Fabrication of Smart Home With Internet of Things Enabled Automation System

In this paper, a new smart voltage and current monitoring system (SVCMS) technique is proposed. It monitors a three phase electrical system using an Arduino platform as a microcontroller to read the voltage and current from sensors and then wirelessly send the measured data to monitor the results using a new Android application. The integrated SVCMS design uses an Arduino Nano V3.0 as the microcontroller to measure the results from three voltage and three current sensors and then send this data, after calculation, to the Android smartphone device of an end user using Bluetooth HC-05. The Arduino Nano V3.0 controller and Bluetooth HC-05 are a cheap microcontroller and wireless device, respectively. The new Android smartphone application that monitors the voltage and current measurements uses the open source MIT App Inventor 2 software. It allows for monitoring some elementary fundamental voltage power quality properties. An effort has been made to investigate what is possible using available off-the-shelf components and open source software.

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A Smart Voltage and Current Monitoring System for Three Phase Inverters Using an Android Smartphone Application.

Recognition of Blue Traffic Signs Enhanced by Aggregating Fragmentarily Segmented Sign Images

Driver’s physical condition may contribute to traffic accident when it is in a lethargic state that result in faulty maneuvers of his vehicles. Due to these possibilities, many research focuses in developing automatic speed control systems that considers the environment condition, with which relieving the human from the control task when the driver’s judgement is not suitable for the environmental condition. Time-change-fuzzy-sets has been proven successful in analyzing safety level in traffic condition. This paper proposes an intelligent vehicle control system based on Time-Change-Fuzzy that can safely transit a moving vehicle from its original lane towards the emergency lane automatically when the driver is in lethargic state and the effectiveness was evaluated in a series of simulation.

Time-Change-Fuzzy-based Intelligent Vehicle Control System for Safe Emergency Lane Transition During Driver Lethargic State

The field of brain computer interference has grown rapidly with the purpose of reading a human's mind, generating a certain output, controlling objects with this output and having an automated understanding of human reactions and responses to the surrounding environment Electroencephalography (EEG) may provide an insight into human behavior and attention There is a huge need in different fields, eg psychology and medical, for an automated approach that helps the psychologist in dealing with the massive amount of data in a sensible period This research study proposes an approach to extract some features from infant EEG signals and evaluate the effect of the bad or good EEG channels on different EEG segments The achieved work will provide an insight about the employment of the most suitable features to represent the EEG data The acquired infant EEG data will be deployed to build an objectively evaluated framework that has the ability to provide an automated understanding of the infants' behavior, underpin the infant specialists in analyzing the infant attentions for stimuli within different environments

Evaluating bad and good EEG segments based on extracted features: Towards an automated understanding of infant behavior and attention

This paper proposes an algorithm for labeling and segmenting blue traffic signs indicating directions. In order to discriminate blue signs from blue sky background, opponent color filters, which are found in our visual system, and seeded region growing algorithm are employed. Since blue signs are occasionally segmented as several disconnected parts, a connecting algorithm for fragmented signs is devised. After segmentation, a verification step takes place to test if the segmented blue object is a sign candidate or not. After that white objects within the blue object are segmented. Finally the white objects are classified by matching them to templates of arrow patterns according to geometrical features. If no arrow pattern is matched, they are rejected. Classification is made using a decision tree. Processing time was about 100-160 ms/frame with 2.20GHz notebook PC. The system could segment all blue signs from the blue sky background. Precision rate of recognition was 71%, recall rate was 94% and F-measure was 81%.

Real-Time Recognition of Blue Traffic Signs From Blue Sky Background

Autonomous vehicles are one of the promising solutions to reduce traffic crashes and improve mobility and traffic system. An autonomous vehicle is preferable because it helps in reducing the need for redesigning the infrastructure and because it improves the vehicle power efficiency in terms of cost and time taken to reach the destination. Autonomous vehicles can be divided into 3 types: Aerial vehicles, ground vehicles and underwater vehicles. General, four basic subsystems are integrated to enable a vehicle to move by itself which are: Position identifying and navigation system, surrounding environment situation analysis system, motion planning system and trajectory control system. In this paper, a review on autonomous vehicles and their related technological applications is presented to highlight the aspects of this industry as a part of industry 4.0 concept. Moreover, the paper discusses the best autonomous driving systems to be applied on our wheelchair project which aims at converting a manual wheelchair to a smart electric wheelchair

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Mohammed Hayyan Alsibai

Papers

Recognition of Blue Traffic Signs Enhanced by Aggregating Fragmentarily Segmented Sign Images

Time-Change-Fuzzy-based Intelligent Vehicle Control System for Safe Emergency Lane Transition During Driver Lethargic State

Evaluating bad and good EEG segments based on extracted features: Towards an automated understanding of infant behavior and attention

Real-Time Recognition of Blue Traffic Signs From Blue Sky Background

A Review on Autonomous Driving Systems