Ravindranath Kokku

Demultiplexing activities of daily living in IoT enabled smarthomes

Powered by the emergence of the Internet of Things, smart homes containing a variety of sensors and actuators are expected to monitor and react to the activities of the residents with the goal of improving convenience, comfort and safety. However, in typical home settings, each human Activity of Daily Living (ADL) generates events from multiple sensors, and each sensor is triggered by multiple ADLs. Consequently, achieving high detection accuracy in these complex environments requires large amounts of training data for every possible multiplexing scenario, making it a complex problem. In this paper, we propose a data driven three-step de-multiplexing approach that simplifies the ADL recognition problem by first segmenting the event stream into periods of interest, before feeding to a classifier. We mine datasets to identify salient features which allow us to achieve a good segmentation. Extensive evaluation on ten public datasets shows that our approach achieves upto 77% segmentation accuracy, and a activity detection accuracy within 91% of the best possible.

Case Studies in Managing Traffic in a Developing Country with Privacy-Preserving Simulation as a Service

Simulation is known to be an effective technique to understand and manage traffic in cities of developed countries. However, in developing countries, traffic management is lacking due to a wide diversity of vehicles on the road, their chaotic movement, little instrumentation to sense traffic state and limited funds to create IT and physical infrastructure to ameliorate the situation. Under these conditions, in this paper, we present our approach of using the Megaffic traffic simulator as a service to gain actionable insights for two use-cases and cities in India, a first. Our approach is general to be readily used in other use cases and cities, and our results give new insights: (a) using demographics data, traffic demand can be reduced if timings of government offices are altered in Delhi, (b) using a mobile companys Call Data Record (CDR) data to mine trajectories anonymously, one can take effective traffic actions while organizing events in Mumbai at local scale.