Development of Economic Water Usage Sensor and Cyber-Physical Systems Co-Simulation Platform for Home Energy Saving

In this thesis, two Cyber-Physical Systems (CPS) approaches were considered to reduce residential building energy consumption. First, a flow sensor was developed for residential gas and electric storage water heaters. The sensor utilizes unique temperature changes of tank inlet and outlet pipes upon water draw to provide occupant hot water usage. Post processing of measured pipe temperature data was able to detect water draw events. Conservation of energy was applied to heater pipes to determine relative internal water flow rate based on transient temperature measurements. Correlations between calculated flow and actual flow were significant at a 95% confidence level. Using this methodology, a CPS water heater controller can activate existing residential storage water heaters according to occupant hot water demand. The second CPS approach integrated an open-source building simulation tool, EnergyPlus, into a CPS simulation platform developed by the National Institute of Standards and Technology (NIST). The NIST platform utilizes the High Level Architecture (HLA) co-simulation protocol for logical timing control and data communication. By modifying existing EnergyPlus co-simulation capabilities, NIST’s open-source platform was able to execute an uninterrupted simulation between a residential house in EnergyPlus and an externally connected thermostat controller. The developed EnergyPlus wrapper for HLA co-simulation can allow active replacement of traditional real-time data collection for building CPS development. As such, occupant sensors and simple home CPS product can allow greater residential participation in energy saving practices, saving up to 33% on home energy consumption nationally

Automated design analysis, assembly planning and motion study analysis using immersive virtual reality

Previous research work at Heriot-Watt University using immersive virtual reality (VR) for cable harness design showed that VR provided substantial productivity gains over traditional computer-aided design (CAD) systems. This follow-on work was aimed at understanding the degree to which aspects of this technology were contributed to these benefits and to determine if engineering design and planning processes could be analysed in detail by nonintrusively monitoring and logging engineering tasks. This involved using a CAD-equivalent VR system for cable harness routing design, harness assembly and installation planning that can be functionally evaluated using a set of creative design-tasks to measure the system and users' performance. A novel design task categorisation scheme was created and formalised which broke down the cable harness design process and associated activities. The system was also used to demonstrate the automatic generation of usable bulkhead connector, cable harness assembly and cable harness installation plans from non-intrusive user logging. Finally, the data generated from the user-logging allowed the automated activity categorisation of the user actions, automated generation of process flow diagrams and chronocyclegraphs

Classification Algorithms Framework (CAF) to enable Intelligent Systems using JetBrains MPS domain-specific languages environment

This paper describes the design and development of a Classification Algorithms Framework (CAF) using the JetBrains MPS domain-specific languages (DSLs) development environment. It is increasingly recognized that the systems of the future will contain some form of adaptivity therefore making them intelligent systems as opposed to the static systems of the past. These intelligent systems can be extremely complex and difficult to maintain. Descriptions at higher-level of abstraction (system-level) have long been identified by industry and academia to reduce complexity. This research presents a Framework of Classification Algorithms at system-level that enables quick experimentation with several different algorithms from Naive Bayes to Logistic Regression. It has been developed as a tool to address the requirements of British Telecom’s (BT’s) data-science team. The tool has been presented at BT and JetBrains MPS and feedback has been collected and evaluated. Beyond the reduction in complexity through the system-level description, the most prominent advantage of this research is its potential applicability to many application contexts. It has been designed to be applicable for intelligent applications in several domains from business analytics, eLearning to eHealth, etc. Its wide applicability will contribute to enabling the larger vision of Artificial Intelligence (AI) adoption in context

The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

Education and training needs, methods, and tools

The importance of education and training in the domain of power and energy systems targeting the topics of cyber-physical energy systems/smart grids is discussed in this chapter. State-of-the art laboratory-based and simulation-based tools are presented, aiming to address the new educational needs