Luke Russell

Low-cost, rapid prototyping of IMU and pressure monitoring system using an open source hardware design

Open source hardware is a type of hardware where the schematics and designs are made unrestricted and available to all. They are often accompanied by open source software. This can bring reliability, ease of debugging, and modular development for rapid prototyping using pre-written libraries. Merits of using open source hardware are discussed and then applied to a portable sensor system based on the open hardware Arduino-derived Jeenode microcontroller board. The system uses an inertial measurement unit (IMU) and seamless integration of other sensors, including a piezo-resistive pressure sensor. It is shown that open source hardware can help to increase rapid development, reduce costs, and encourage further development.

Stride time estimation: Realtime peak detection implemented on an 8-bit, portable microcontroller

Falls are a threat of great magnitude for the aging population. Methods, and the pursuit thereof to improve anticipatory prediction of falls, could reduce incidence of injury thereby lowering associated costs of healthcare. Gait monitoring is seen as a reliable area to help decipher potential warning signs as precursors to falls. Stride time is one such parameter, in particular to monitor a patient and recognize variation between stride times. Demographic trends show increasing numbers of older adults. Prevention and avoidance of injurious falls is a key area to impact sustained vigour and quality of life for seniors. Couple this with prolonged ability to maintain autonomy and remain living at home. This combination can profoundly extend distribution of healthcare resources. A portable, inexpensive, low power 8-bit microcontroller in conjunction with an accelerometer and gyroscope is used to implement an algorithm on the microcontroller board to perform peak detection and calculate the gait parameter, stride time, of a patient in real time. This information then transmits via Bluetooth®.

Smart environments using near-field communication and HTML5

Home health care and home automation increasingly allows more seniors to maintain independence, and remain longer in their own homes. Similarly, a post-surgical patient may be discharged from a medical facility to their house, which electronically facilitates their recuperation and promotes recovery. Smart environments are making the task of providing assistive technology in the home easier and more affordable. Near-field communication (NFC) has become popular in recent years. Increasing uptake of NFC-enabled smartphones has opened a new avenue to facilitate creation of a smart environment without the need for significant infrastructure. HTML5 is the latest version of the hypertext markup language, with unique code that enables access to advanced features on a smartphone. Proprietary apps can potentially be inconvenient and inconsistent and may even decrease uptake of the technology. In this paper, we propose a new methodology to enable NFC tags and NFC smartphones in conjunction with HTML5 backbone code, to be used for smart environments in home health care applications without the need for specific applications to be installed on the smartphone. Results show significant promise with just the built in phone software with use of NFC and HTML5 for various applications of smart environments. In many common tasks in a smart environment that increase patient safety, NFC tags can be not only informative, but an integral component of the system by triggering specific HTML5 code to provide appropriate responses - without the need to install specialized apps as long as the NFC is enabled in the mobile device.

Personalization Using Sensors for Preliminary Human Detection in an IoT Environment

In Internet of Things (IoT), there are many future applications in smart environments. This paper first presents a possible scenario of a family making use of the IoT in their daily living, and then work leading to integration of unobtrusive sensors in the smart environment is discussed. In the applications discussed, Bluetooth connections linked and connected the sensors that were used in the wireless sensor network as an intuitive sensor communication platform. The paper presents results of a methodology and experimentation for human identification using sensors and microcontrollers and discusses how this can lead to integration and increased personalization within an IoT smart environment using only unobtrusive sensors.

Sensor modality shifting in IoT deployment: Measuring non-temperature data using temperature sensors

Deployment of sensor systems for smart, Internet of Things (IoT) environments may be subject to high cost, physical limitations, building modification regulations, or lengthy processes. Flexibility of sensor type choice can lead to overcoming various constraints. Very low cost, easily deployable sensors can provide data other than that for which it was designed. In this paper, we use temperature sensors, rather than the customarily used job-specific sensors, to measure the mechanical events of opening of a fridge door and the physical event of water flow in a pipe. A given sensor that measures a particular parameter can instead use a different, alternative low cost sensor to answer the same end question: the means by which the answer is derived differs, and thus the sensors modality shifts. We show results of replacing flow meters in pipes and mechanical switches in refrigerator doors with temperature sensors, thereby shifting the modality of the temperature sensor from measuring the room temperature to measuring other physical parameters.

Posture sensing using a low-cost temperature sensor array

Posture identification is an example of one of many physiological characteristics that can be used to determine a variety of health parameters. Pressure mats and camera analysis are common methodologies to determine posture of a subject in a chair. In this paper, we show results of a laboratory study of how we can determine posture of a subject using various arrays of multiple low-cost temperature sensors per section or characteristic to be determined. This can be a standalone occupancy and posture system, or can be fused with data from other technologies to validate data from pressure or visual-based systems. The system was tested with different types of furniture such as various styles of chairs, armrests, cushions, and beds.

Low-cost, rapid deployment, over-the-top HVAC and room thermal efficiency system using open source hardware design

Heating, ventilation, and air conditioning (HVAC) systems can consume a large percentage of the energy used in a typical building. Intelligent building automation systems (BAS) are widely deployed to enable more efficient HVAC utilization, thus reducing the energy consumed. Enhanced data requires distributed sensing. We propose an instrumentation system for a low-cost, over-the-top efficiency monitor using the open-source hardware design to enable rapid deployment and live monitoring of temperature within zones such as rooms. This enables evaluation of HVAC system efficiency, and building parameter monitoring in that room. This paper presents our HVAC, thermal, and building parameter monitoring system design and considerations using an open-source hardware approach for fast customizations. We show results of monitoring two buildings including distributed sensing within rooms, and discuss intelligence gathered through use of this system as a precursor towards a fully automated efficiency evaluation and measurement.

Sensor Node to Improve Resiliency and Monitoring in Smart Grids: Taking the Lab to Field in Industry

Sensors and data analytics have a tremendous potential to improve the resilience of the electricity system. Improving the analytics in a smart grid, and providing information to operators so that problems can be resolved quickly, may serve to improve the resiliency of the electricity system. Effective use of sensors and analytics will enable more timely a response, and more efficient use of personnel, specialty equipment, and site location specifics because of better information for deployment teams to address damage. Detection of physical characteristics such as vibration, ice build up, hot spots, aging and deterioration of assets/equipment, metal fatigue and other considerations could prevent disruptions. In cold climates, ice storms can cause outages, and extreme weather events are constantly a threat to electricity towers. A system was developed to collect information from sensors, as well as relevant analytics to detect abnormalities to address damage, and for operator visualizations screens.