Learn More
Non-intrusive appliance load monitoring is the process of dis-aggregating a household's total electricity consumption into its contributing appliances. In this paper we propose an approach by which individual appliances can be iteratively separated from an aggregate load. Unlike existing approaches, our approach does not require training data to be(More)
Non-intrusive appliance load monitoring is the process of disaggregating a household's total electricity consumption into its contributing appliances. In this paper we propose an unsupervised training method for non-intrusive monitoring which, unlike existing supervised approaches, does not require training data to be collected by sub-metering individual(More)
Non-intrusive appliance load monitoring is the process of breaking down a house-hold's total electricity consumption into its contributing appliances. In this paper we propose an approach by which individual appliances are iteratively separated from the aggregate load. Our approach does not require training data to be collected by sub-metering individual(More)
In this demonstration, we present a scalable low-cost solution to provide personalized home heating advice to house-holds. Our solution uses a specially designed USB temperature logger, placed on top of the thermostat, to infer the operation of the heating system indirectly. Using additional external temperature data, available through the internet, it(More)
Minimizing the energy consumed by heating, ventilation, and air conditioning (HVAC) systems of residential buildings without impacting occupants’ comfort has been highlighted as an important artificial intelligence (AI) challenge. Typically, approaches that seek to address this challenge use a model that captures the thermal dynamics within a(More)
Automated essay grading or scoring systems are not more a myth they are reality. As on today, the human written (not hand written) essays are corrected not only by examiners / teachers also by machines. The TOEFL exam is one of the best examples of this application. The students' essays are evaluated both by human & web based automated essay grading system.(More)
Latent force models (LFM) are principled approaches to incorporating solutions to differential equations within non-parametric inference methods. Unfortunately, the development and application of LFMs can be inhibited by their computational cost, especially when closed-form solutions for the LFM are unavailable, as is the case in many real world problems(More)
Detection of defective pixels in solid-state detectors/sensor arrays has received limited research attention. Few approaches currently exist for detecting the defective pixels using real images captured with cameras equipped with such detectors, and they are ad hoc and limited in their applicability. In this paper, we present a probabilistic novel(More)
Swarm Robotics is an area of active research interest where groups of robots coordinate and perform collective tasks. Existing approaches to Learning and Collective Decision Making amongst a group of robots is complex. In this paper, we propose a simple model of learning and collective decision making in honey bees engaged in foraging for suitable(More)