Low cost non-intrusive home energy monitoring

This thesis presents a low cost non-intrusive home energy monitor built on top of Non-Intrusive Load Monitoring (NILM) concepts and techniques. NILM solutions are already considered low cost alternatives to the big majority of existing commercial energy monitors but the goal here is to make its cost even lower by using a mini netbook as a whole in one solution. The mini netbook is installed in the homes main circuit breaker and computes power consumption by reading current and voltage from the built-in sound card. At the same time, feedback to the users is provided using the 11’’ LCD screen as well as other built-in I/O modules. Our meter is also capable of detecting changes in power and tries to find out which appliance lead to that change and it is being used as part of an eco-feedback platform that was build to study the long terms of energy eco-feedback in individuals. In this thesis the steps that were taken to come up with such a system are presented, from the basics of AC power measurements to the implementation of an event detector and classifier that was used to disaggregate the power load. In the last chapter results from some validation tests that have been performed are presented in order to validate the experiment. It is believed that such a system will not only be important as an energy monitor, but also as an open system than can be easily changed to accommodate and test new or existing nonintrusive load monitoring techniques.

Characterization of micro-bubble size distribution and flow configuration in DAF contact zone by a non-intrusive image analysis system and tracer tests

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ultra-Low Power and Non-intrusive Wireless Monitoring for Smart Buildings

Wireless Sensor Networks (WSNs) offer a new solution for distributed monitoring, processing and communication. First of all, the stringent energy constraints to which sensing nodes are typically subjected. WSNs are often battery powered and placed where it is not possible to recharge or replace batteries. Energy can be harvested from the external environment but it is a limited resource that must be used efficiently. Energy efficiency is a key requirement for a credible WSNs design. From the power source's perspective, aggressive energy management techniques remain the most effective way to prolong the lifetime of a WSN. A new adaptive algorithm will be presented, which minimizes the consumption of wireless sensor nodes in sleep mode, when the power source has to be regulated using DC-DC converters. Another important aspect addressed is the time synchronisation in WSNs. WSNs are used for real-world applications where physical time plays an important role. An innovative low-overhead synchronisation approach will be presented, based on a Temperature Compensation Algorithm (TCA). The last aspect addressed is related to self-powered WSNs with Energy Harvesting (EH) solutions. Wireless sensor nodes with EH require some form of energy storage, which enables systems to continue operating during periods of insufficient environmental energy. However, the size of the energy storage strongly restricts the use of WSNs with EH in real-world applications. A new approach will be presented, which enables computation to be sustained during intermittent power supply. The discussed approaches will be used for real-world WSN applications. The first presented scenario is related to the experience gathered during an European Project (3ENCULT Project), regarding the design and implementation of an innovative network for monitoring heritage buildings. The second scenario is related to the experience with Telecom Italia, regarding the design of smart energy meters for monitoring the usage of household's appliances.

Non-intrusive pressure measurement in microchannels

A non-intrusive interferometric measurement technique has been successfully developed to measure fluid compressibility in both gas and liquid phases via refractive index (RI) changes. The technique, consisting of an unfocused laser beam impinging a glass channel, can be used to separate and quantify cell deflection, fluid flow rates, and pressure variations in microchannels. Currently in fields such as microfluidics, pressure and flow rate measurement devices are orders of magnitude larger than the channel cross-sections making direct pressure and fluid flow rate measurements impossible. Due to the non-intrusive nature of this technique, such measurements are now possible, opening the door for a myriad of new scientific research and experimentation. This technique, adapted from the concept of Micro Interferometric Backscatter Detection (MIBD), boasts the ability to provide comparable sensitivities in a variety of channel types and provides quantification capability not previously demonstrated in backscatter detection techniques. Measurement sensitivity depends heavily on experimental parameters such as beam impingement angle, fluid volume, photodetector sensitivity, and a channel’s dimensional tolerances. The current apparatus readily quantifies fluid RI changes of 10-5 refractive index units (RIU) corresponding to pressures of approximately 14 psi and 1 psi in water and air, respectively. MIBD reports detection capability as low as 10-9 RIU and the newly adapted technique has the potential to meet and exceed this limit providing quantification in the place of detection. Specific device sensitivities are discussed and suggestions are provided on how the technique may be refined to provide optimal quantification capabilities based on experimental conditions.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

Development of a non-intrusive heat transfer coefficient gauge and its application to high pressure die casting Effect of the process parameters

A heat transfer coefficient gauge has been built, obeying particular rules in order to ensure the relevance and accuracy of the collected information. The gauge body is made out of the same materials as the die casting die (H13). It is equipped with six thermocouples located at different depths in the body and with a sapphire light pipe. The light pipe is linked to an optic fibre, which is connected to a monochromatic pyrometer. Thermocouples and pyrometer measurements are recorded with a data logger. A high pressure die casting die was instrumented with one such gauge. A set of 150 castings was done and the data recorded. During the casting, some process parameters have been modified such as piston velocity, intensification pressure, delay before switch to the intensification stage, temperature of the alloy, etc.... The data was treated with an inverse method in order to transform temperature measurements into heat flux density and heat transfer coefficient plots. The piston velocity and the initial temperature of the die seem to be the process parameters that have the greatest influence on the heat transfer. (c) 2005 Elsevier B.V. All rights reserved.

Development of a non-intrusive system to monitor radial pulse wave velocity

Understanding arterial distensibility has shown to be important in the pathogenesis of cardiovascular abnormalities like hypertension. It is also known that arterial pulse wave velocity (PWV) is a measure of the elasticity or stiffness of peripheral arterial blood vessels. However, it generally requires complex instrumentations to have an accurate measurement and not suited for continual monitoring. In this paper, it describes a simple and non-intrusive method to detect the cardiovascular pulse from a human wrist above the radial artery and a fingertip. The main components of this proposed method are a piezoelectric transducer and a photo-plethysmography circuitry. 5 healthy adults (4 male) with age ranging from 25 to 38 years were recruited. The timing consistency of the detected pulsations is first evaluated and compared to that obtained from a commercial electrocardiogram. Furthermore, the derived PWV is then assessed by the predicted values attained from regression equations of two previous similar studies. The results show good correlations (p < 0.05) and similarities for the former and latter respectively. The simplicity and non-invasive nature of the proposed method can be attractive for even younger or badly disturbed patients. Moreover, it can be used for prolonged monitoring for the comfort of the patients.

Élastographie vasculaire non-intrusive : vers un outil complémentaire pour la caractérisation de l'athérosclérose carotidienne

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Évaluation et dépendance angulaire de l'estimateur Lagrangien en élastographie vasculaire non-intrusive

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Élastographie vasculaire non-intrusive : vers un outil complémentaire pour la caractérisation de l'athérosclérose carotidienne

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Évaluation et dépendance angulaire de l'estimateur Lagrangien en élastographie vasculaire non-intrusive

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Hydroacoustic surveys: a non-destructive approach to monitoring fish distributions at National Marine Sanctuaries

The science of fisheries acoustics and its applicability to resource management have evolved over the past several decades. This document provides a basic description of fisheries acoustics and recommendations on using this technology for research and monitoring of fish distributions and habitats within sanctuaries. It also describes recent efforts aimed at applying fisheries acoustics to Gray’s Reef National Marine Sanctuary (GRNMS) (Figure 1). Historically, methods to assess the underwater environment have included net trawls, diver censuses, hook and line, video, sonar and other techniques deployed in a variety of ways. Fisheries acoustics, using active sonar, relies on the physics of sound traveling through water to quantify the distribution of biota in the water column. By sending a signal of a given frequency through the water column and recording the time of travel and the strength of the reflected signal, it is possible to determine the size and location of fish and estimate biomass from the acoustic backscatter. As a fisheries assessment tool, active hydroacoustics technology is an efficient, non-intrusive method of mapping the water column at a very fine spatial and temporal resolution. It provides a practical alternative to bottom and mid-water trawls, which are not allowed at GRNMS. Passive acoustics, which uses underwater hydrophones to record man-made and natural sounds such as fish spawning calls and sounds produced by marine mammals for communication and echolocation, can provide a useful, complementary survey tool. This report primarily deals with active acoustics, although the integration of active and passive acoustics is addressed as well. (PDF contains 32 pages)