INTERNET OF THINGS
INTERNET OF THINGS
1.BSN-Care: A Secure IoT-based Modern Healthcare System Using Body Sensor Network
BSN-Care: A Secure IoT-based Modern Healthcare System Using Body Sensor Network
Advances in information and communication technologies have led to the emergence of Internet of Things (IoT). In the modern health care environment, the usage of IoT technologies brings convenience of physicians and patients since they are applied to various medical areas (such as real-time monitoring, patient information management, an healthcare management). The body sensor network (BSN) technology is one of the core technologies of IoT developments in healthcare system, where a patient can be monitored using a collection of tiny-powered and lightweight wireless sensor nodes. However, development of this new technology in healthcare applications without considering security makes patient privacy vulnerable. In this article, at first we highlight the major security requirements in BSN based modern healthcare system. Subsequently, we propose a secure IoT based healthcare system using BSN, called BSN-Care, which can efficiently accomplish those requirements.
2.Design and Implementation of Interoperable IoT Healthcare System Based on International Standards
Design and Implementation of Interoperable IoT Healthcare System Based on International Standards
In Internet of Things (IoT) environment, IoT devices are limited to power supply, CPU capacity, memory, etc. and have a constrained network performance such as bandwidth, wireless channel, throughput, payload, etc., the resources of IoT devices however can be shared by other IoT devices. Specially, in IoT healthcare service, the way of management and interoperability of patient-related and device information are very important. In this paper, we propose the design and implementation of an IoT healthcare system using ISO/IEEE 11073 PHD (Personal Healthcare Device) and CoAP (Constrained Application Protocol) standards in order to enhance the interoperability and reduce the data loss between the devices and measured information while in transmission. To demonstrate the proposed architecture, we implement comparative performance evaluation between HTTP and CoAP in terms of the number of packets in one transaction, the number of packets by data loss rate in during transmission and a syntax usage between XML and JSON.
3.Developing an Open Access Monitoring Device for Off-Grid Renewables
Developing an Open Access Monitoring Device for Off-Grid Renewables
Electricity access is a key driver for developing a modern society. The use of locally generated renewable energy can overcome limitations of expensive grid infrastructure. However, there are still barriers to access particularly for the rural poor in the global south. When individuals or communities invest in electricity provision it is important to know how well the system is performing. Commercial monitoring systems have been developed for large scale renewable energy systems. The cost of these can outweigh the cost of a small decentralised renewable energy system. This paper describes the development of a low cost data logger that is going to be used to monitor the system performance of small photovoltaic nano-grids in Kenya and Bangladesh. The device performs within the expected range for the current, voltage, temperature and irradiance sensors. Data from the data logger device is sent via GPRS to a website where it can be accessed as real time graphical displays and data files.
4.Target Localization using RGB-D Camera and LiDAR Sensor Fusion for Relative Navigation
Target Localization using RGB-D Camera and LiDAR Sensor Fusion for Relative Navigation
This paper describes a novel approach to estimating the position of target based on fusion of RGB-depth camera and 2D light detection and ranging (LiDAR) sensor measurements. In the proposed approach, the 3D and 2D position information of target measured by RGB-D camera and LiDAR sensor respectively are utilized to find location of target by incoporating visual tracker, depth information and vision- LiDAR low-level fusion algorithm (e.g., extrinsic calibration). Registration error correction of multiple measurements from both RGB-D camera and LiDAR sensors is executed in order to carry out data fuison. Then, results of local noisy position measuments are fused using track-to-track fusion algorithm. The experimental verification results are compared to position data from VICON motion capture and the results show that the performance of the proposed approach is better than each sensor’s localization result in view of noise intensity.
5.Secure Management of Low Power Fitness Trackers
Secure Management of Low Power Fitness Trackers
The increasing popular interest in personal telemetry, also called the Quantified Self or “lifelogging”, has induced a popularity surge for wearable personal fitness trackers. Fitness trackers automatically collect sensor data about the user throughout the day, and integrate it into social network accounts. Solution providers have to strike a balance between many constraints, leading to a design process that often puts security in the back seat. Case in point, we reverse engineered and identified security vulnerabilities in Fitbit Ultra and Gammon Forerunner 610, two popular and representative fitness tracker products.We introduce FitBite and GarMax, tools to launch efficient attacks against Fitbit and Garmin. We devise SensCrypt, a protocol for secure data storage and communication, for use by makers of affordable and lightweight personal trackers. SensCrypt thwarts not only the attacks we introduced, but also defends against powerful JTAG Read attacks. We have built Sens.io, an Arduino Uno based tracker platform, of similar capabilities but at a fraction of the cost of current solutions. On Sens.io, SensCrypt imposes a negligible write overhead and significantly reduces the end-to-end sync overhead of Fitbit and Garmin.
6.Simple ambulatory gait monitoring system using a single IMU for various daily-life gait activities
Simple ambulatory gait monitoring system using a single IMU for various daily-life gait activities
The gait monitoring during daily-life is promising measure to predict mortality, functional decline and fall risk, and classification of gait activities has the possibility for further clinical usage. This paper introduces a simple ambulatory gait monitoring system using a single IMU attached on foot. The system consist of gait parameter estimation and simple gait activity classification algorithm based on characteristics of foot behavior in major gait activities of daily-life, such as leveled, ramp, and stair walk. Through experiment with five healthy subjects, the estimated gait parameters and the classification were verified by motion capture system and video recordings. The results showed that the proposed IMU-based gait monitoring is applicable with leveled, ramp, and stair walk, and its accuracy is acceptable comparing with existing complicated gait monitoring methods.
7.Turning the internet of (my) things into a remote controlled laboratory
Turning the internet of (my) things into a remote controlled laboratory
In this paper we use a locally developed adaptive watering system as an example of a remote controlled laboratory (RCL) developed with standard open hardware and using libraries taken from the e-lab. This experiment is a particular case that could benefit from a large number of RCLs proposing different water budget strategies, allowing the studies of the best controller algorithm to save water. The water consumption log can be monitored in real-time and served to any user as a distributed remote laboratory with support of a Raspberry PI and a web connection, using an open source Arduino board and custom made shield. The ultimate goal of RCLs will be achieved when anyone can easily publish their own experiment in the WWW.