Anthony Schoofs

Real-Time Recognition and Profiling of Appliances through a Single Electricity Sensor

Sensing, monitoring and actuating systems are expected to play a key role in reducing buildings overall energy consumption. Leveraging sensor systems to support energy efficiency in buildings poses novel research challenges in monitoring space usage, controlling devices, interfacing with smart energy meters and communicating with the energy grid. In the attempt of reducing electricity consumption in buildings, identifying individual sources of energy consumption is key to generate energy awareness and improve efficiency of available energy resources usage. Previous work studied several non-intrusive load monitoring techniques to classify appliances; however, the literature lacks of an comprehensive system that can be easily installed in existing buildings to empower users profiling, benchmarking and recognizing loads in real-time. This has been a major reason holding back the practice adoption of load monitoring techniques. In this paper we present RECAP: RECognition of electrical Appliances and Profiling in real-time. RECAP uses a single wireless energy monitoring sensor easily clipped to the main electrical unit. The energy monitoring unit transmits energy data wirelessly to a local machine for data processing and storage. The RECAP system consists of three parts: (1) Guiding the user for profiling electrical appliances within premises and generating a database of unique appliance signatures; (2) Using those signatures to train an artificial neural network that is then employed to recognize appliance activities (3) Providing a Load descriptor to allow peer appliance benchmarking. RECAP addresses the need of an integrated and intuitive tool to empower building owners with energy awareness. Enabling real-time appliance recognition is a stepping-stone towards reducing energy consumption and allowing a number of major applications including load-shifting techniques, energy expenditure breakdown per appliance, detection of power hungry and faulty appliances, and recognition of occupant activity. This paper describes the system design and performance evaluation in domestic environment.

Remote Electricity Actuation and Monitoring mote

This work presents the design and evaluation of the REAM (Remote Electricity Actuation and Monitoring) node based around the modular Tyndall Mote platform. The REAM node enables the user to remotely actuate power to a mains power extension board while sampling the current, voltage, power and power factor of the attached load. The node contains a current transformer interfaced to an Energy Metering IC which continuously samples current and voltage. These values are periodically read from the part by a PIC24 microcontroller, which calculates the RMS current and voltage, power factor and overall power. The resultant values can then be queried wirelessly employing the Tyndall 802.15.4 compliant wireless module.

Appliance activity monitoring using wireless sensors

Appliance load monitoring systems aim to achieve per appliance energy decomposition. Such systems however lack automated set-up, which precludes widespread roll-outs. This work illustrates how human supervision can be reduced to a strict minimum; appliance activity states are captured with cheap wireless sensors, which enables accurate automated energy data annotation. This paper demonstrates the accuracy of this technique via an intuitive graphical user interface.

NetBem: business equipment energy monitoring through network auditing

Modern office buildings are fully equipped and furnished spaces with arrangements including networked business equipment, such as PC-class machines, copiers, wireless routers and fax machines, and other electrical equipment such as home appliances e.g. coffee machines, and appliances for environmental comfort e.g. electric heaters. The unique characteristics of networked business equipment are well-defined usage pattern, low-power current draw, and connectivity to the local area network (LAN). Business equipment is generally used over working hours adding up to important costs, motivating the need for a system capable of tracking equipment usage and associated energy expenditure, as well as identifying cost saving opportunities. Techniques for monitoring power loads are generally based on power step edge detection, and cannot be applied to business equipment due to the low power consumption of individual devices. This paper presents NetBem, a novel energy monitoring technique ad hoc to office buildings, capturing the contribution of networked business equipment to a power load via side-band detection of the equipments operating state through the LAN. The technique is presented, and results from experiments within the School of Computer Science and Informatics at University College Dublin in Ireland are given.

Portability in MAC protocol and transceiver software implementations for LR-WPAN platforms

In a variety of emerging networked computing system domains over the years, there have been bursts of activity on new medium access control (MAC) protocols, as new communication transceiver technologies with greater data‐movement performance or lower power dissipation have been introduced. To enable implementations flexible to evolving standards and improving application‐domain insight, such MAC protocols are typically initially implemented in software, and interface between applications or system software, typically executing on an embedded processor or microcontroller, and the evolving radio transceiver hardware. Many challenges exist in implementing MAC protocols across evolving or competing transceiver hardware implementations and processor architectures. Some of these challenges are peculiar to the requirements of MAC protocols, and others are a result of the plethora of system and processor architectures in the embedded systems domain. This article studies the challenges facing software implementations of MAC protocols running on embedded microcontrollers, and interfacing with radio transceiver hardware. Experience with an implementation of the IEEE 802.15.4 MAC across three hardware platforms with different processor, system, and systems software architectures is presented, focusing on implementation approach and interfaces. Pitfalls are pointed out, and guidelines are provided for ensuring that new MAC implementations are easily portable across processor architectures and transceiver hardware. Copyright

Intelligent Middleware for Adaptive Sensing of Tennis Coaching Sessions

In professional tennis training matches, the coachneeds to be able to view play from the most appropriate anglein order to monitor players activities. In this paper, we presenta system which can adapt the operation of a series of camerasin order to maintain optimal system performance based on aset of wireless sensors. This setup is used as a testbed for anagent based intelligent middleware that can correlate data frommany different wired and wireless sensors and provide effectivein-situ decision making. The proposed solution is flexible enoughto allow the addition of new sensors and actuators. Within thissetup we also provide details of a case study for the embeddedcontrol of cameras through the use of Ubisense data.

Portability Versus Efficiency Tradeoffs in MAC Implementations for Microsensor Platforms

Medium access control (MAC) implementations control access of network devices to a transmission medium. For emerging communication protocols, the MAC is typically implemented in software, to enable adaptation to evolving de-facto or industry standards. Software MAC implementations are typically realized as state machines, executing code related to successive MAC states within periodic interrupts. This software construct yields minimal memory footprint and energy efficiency, but the resulting implementations are often tightly coupled to the platforms system software, and are thus nonportable across hardware and system platforms. This article presents an architecture that decouples MAC and system software, enabling portability, while preserving software efficiency.