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Activity recognition in smart environment has been investigated rigorously in recent years. Researchers are enhancing the underlying activity discovery and recognition process by adding various dimensions and functionalities. But one significant barrier still persists which is collecting the ground truth information. Ground truth is very important to initialize a supervised learning of activities...
Activity recognition using smartphone has great potential in many applications like healthcare, obesity management, abnormal behavior detection, public safety and security etc. Typical activity detection systems are built on to recognize a limited set of activities that are present in the training and testing environments. However, these systems require similar data distributions, activity sets and...
The use of smartphone and wearable devices in various sporting events is an optimistic opportunity to profile player's physical fitness and physiological health conditioning attributes. Recently a variety of commercial wearables with respect to different sports are available in the market. As these wearables differ for distinctive sports, it becomes a hassle to effectively profile them for multiple...
Smart home technologies are getting acclaimed for providing a wide variety of functionalities - security, appliance control, HVAC control and remote monitoring. Installation cost and interoperability issues have restricted the adaptability of these technologies. In this demo paper, we demonstrate the design of an interoperable prototype of our smart home system, SenseBox using low-cost embedded device...
Activity recognition has applications in a variety of human-in-the-loop settings such as smart home health monitoring, green building energy and occupancy management, intelligent transportation, and participatory sensing. While fine-grained activity recognition systems and approaches help enable a multitude of novel applications, discovering them with non-intrusive ambient sensor systems pose challenging...
Activity recognition in smart environment has been investigated rigorously in recent years. Researchers are enhancing the underlying activity discovery and recognition process by adding various dimensions and functionalities. But one significant barrier still persists which is collecting the ground truth information. Ground truth is very important to initialize a supervised learning of activities...
Following healthy lifestyle is a key for active living. Regular exercise, controlled diet and sound sleep play an invisible role on the well being and independent living of the people. Sleep being the most durative activities of daily living (ADL) has a major synergistic influence on people's mental, physical and cognitive health. Understanding the sleep behavior longitudinally and its underpinning...
Predicting the occupancy related information in an environment has been investigated to satisfy the myriad requirements of various evolving pervasive, ubiquitous, opportunistic and participatory sensing applications. Infrastructure and ambient sensors based techniques have been leveraged largely to determine the occupancy of an environment incurring a significant deployment and retrofitting costs...
Fine-grained monitoring of everyday appliances can provide better feedback to the consumers and motivate them to change behavior in order to reduce their energy usage. It also helps to detect abnormal power consumption events, long-term appliance malfunctions and potential safety concerns. Commercially available plug meters can be used for individual appliance monitoring but for an entire house, each...
Acoustic sensing has influenced many applications in green building energy management, such as designing multi-modal energy disaggregation algorithms through fine-grained appliance state identifications or efficiently controlling the HVAC system based on the occupancy of the environment. In this demo paper we build a low-cost system prototype using off-the-shelf commercially available hardware (Raspberry...
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