Sounak Dey

Sensor knowledge representation with spatiotemporal annotation: An energy sensor ontology use case

In our smart planet, there are numerous sensors sensing almost everything around us and streaming the sensor data to different data collectors. Storing, categorizing and analyzing sensor data are the key challenging areas with a view to provide their proper usage. Semantic querying on such a deluge of sensor data set imposes another challenge. As queries can be spatial, temporal and thematic in nature, so providing relevant output to each category of queries requires proper understanding of the semantics of the data. Sensor ontologies and their data representation are in place to help understand the semantic to certain extent. Majority of work has focused more on thematic annotation rather spatial and temporal informations about sensors. In this paper, we discuss how to enrich sensor ontologies by incorporating concepts of TimeML and GML to help spatial and temporal analysis and queries.

A Semantic Algorithm Repository and Workflow Designer Tool: Signal Processing Use Case

Recently major emphasis is exerted on development of effective tools and techniques for enriching IoT development environment. Typically an IoT application, for example a health monitoring application, not only requires domain knowledge of a programmer, but also similar knowledge from a medical practitioner, a sensor manufacturer, an infrastructure manager, etc. Such involvement of several experts makes the development process complex, resulting in escalation of time and cost of the effort. Model Driven Development (MDD) has been proposed as a development technique where such problem can be mitigated. This paper presents a system based on the MDD paradigm. As a part of the system, we present a work-flow designer framework, a visual drag and drop interface, where a developer can stitch various functional models recommended from a well-organized, annotated and crowd-sourced semantic repository of algorithms (from various domains), named as Algopedia, to quickly build a semantic workflow and in turn an end to end IoT application.

Demo: A Smart Framework for IoT Analytic Workflow Development

Developing analytical applications for IoT based on sensor signal processing tends to be complicated as applications are executed as sequence of steps comprising of multiple alternative algorithms, including suitable feature extraction modules depending on the goal of the application. Experience shows that developers spend considerable time and effort in performing feature extraction and dimensionality reduction. In this paper we propose a framework based on a relevant case study which allows developers to drag and drop algorithms to create a workflow chain, automatically select the most relevant signal features for the particular analytic application using a training data set to generate a model and deploy the model for use. The method reduces the effort and cost of development which is deemed highly important for the analytics industry.

Spatial query handling in semantic web application: an experience report

Semantically capturing, storing and fetching spatial sensor web data play an important role in various cyber-physical applications. Different tools are available for each of these purposes but all of them have integration and interoperability issues of their own. In this paper, we provide a detailed comparison of different combination of tools and substantiate facts to select the right ones to seamlessly build a semantic web framework which provide effective spatial reasoning and perform semantic query over sensor web data. We also discuss various technical challenges faced during the implementation.

Capturing Semantics of Energy Meter

Numerous sensors are involved in sensing almost everything around us in a cyber-physical system. They generate heterogeneous data which are diverse in format and protocol. Prevailing standards formally define sensor data encodings and provide syntactic interoperability but failed to provide semantic capability required for searching, reasoning, querying on sensors and their observations. The paper extends IEEE SUMO and Onto Sensor to create an ontological structure that captures various sensor concepts and their relationships. It logically classifies sensor information into four major sensor knowledge representation (1) hierarchy (2) data (3) function and (4) data exchange. The proposed sensor ontology has been extended for energy meter as an energy sensor. The represented semantic can be captured through Protégé 4.3.0 and subsequently by OWLXML. Reasoning on the sensor data can be carried out using SWRL.

Electronic Program Guide for RF Fed TV Channels

Electronic Program Guide (EPG) is a feature where the program schedule of the channel is shown as a blended text over the video of the channel user is viewing. In case of STB the hardware is aware of which channel it is tuned to and so its possible to show EPG information easily. But in India where, still 93% of total TV viewers are watching TV from Radio Frequency fed cable, it becomes a challenge to provide EPG, this is because the service providers do not telecast a particular channel in a particular frequency. So in such a scenario, it is not possible to provide EPG easily. In this paper authors have proposed a system that facilitates showing EPG information even in case of RF fed TV. This works by recognizing the channel by identifying the logo of the channel. After the channel is identified, the EPG is obtained by looking up the URL of the particular channel. The EPG is obtained from the URL. The EPG is finally rendered on the video of the channel. The system is developed on a DSP platform that can recognize the channel within a delay of 2 seconds after changing the channel. The system works with 100% accuracy for the channels whose channel logos never disappear from the video. The system cannot work when there is no channel logo in the video which sometimes happen in India when advertisements are shown.

Semantic data exchange between collaborative robots in fog environment: Can CoAP be a choice?

The transition of Internet from human-centric exchanges to the Internet of Things has posed several interesting challenges regarding the communication model and data exchange pattern. The emergence of edge/fog computing as a compute model has further highlighted the need of a uniform model to cater to the inherent heterogeneity of participating devices. In several domains, the devices may range from standard compute and communication devices to gateways/switches, as well as robots/drones and other types of autonomous entities. In scenarios like disaster management, warehouse automation, surveillance etc. use of robots/drones/AGVs/UAVs is steadily increasing in order to minimise potentially hazardous human intervention. Optimality of data exchange and further processing is a desired feature in such scenarios, especially in outdoor disaster situations where availability of the back-end cloud infrastructure can not be guaranteed. In this paper, we demonstrate a real life robotic data exchange model based on Resource Description Framework (RDF). We further perform a comparative analysis of network performance between TCP in Robot Operating System (ROS) and block-wise extension to Constrained Application Layer Protocol (CoAP) for bidirectional exchange of such RDF data in a disaster situation where robotic entities accomplish search and rescue missions in collaboration with fog devices. The causal analysis presented in this paper puts a stepping stone for potential future enhancement of CoAP.

An interactive low cost distance education system over Home Infotainment Platform using color code

Current scenario of distance education system through Television (TV) content providers Set Top Box (STB) is entirely dependent on the channel broadcasting of the Direct To Home (DTH) provider and is one way thus not interactive. The real time question-answer session is entirely dependent on the other input systems like mobile etc. The authors propose a color code based interactive distance education system on Television(TV) using a connected Home Infotainment Platform (HIP) device capable of connecting a remote data server and capable of decoding video frames to extract color code for metadata. According to our proposed methodology, HIP device will reside between TV set and DTH service providers STB and by extracting color coded metadata from video frames it is able to connect to a remote server where the questions-answer session details is stored. This connection is based on simple internet connection. On fetching, this question-answer session will be rendered in an interactive way on TV screen following defined time intervals and will take and send students response to remote server for evaluation through the same internet communication channel. Since most of the question answer data will consist of text data so this scheme will also be very effective for regions having low data rate connectivity. This system also enables students to send their query or questions to same server at any point of video lecture.

An interactive social boarding system using home infotainment platform

The authors propose a customer interactive and connected boarder experience for the hospitality industry using the in-room TV set and a Home Infotainment Platform (HIP) connected to the same. This aims at building an interactive and social platform for interacting with the Hotel services and facilities. It also facilitates the replacement of the EPABX in the room with more interactive means for providing services including but not restricted to restaurant table booking, conference room booking, wake-up call service and external communications. This will lead to a more cost-effective deployment of services with a richer feature-set.