Md. Anisur Rahman

Augmenting Context Awareness by Combining Body Sensor Networks and Social Networks

Due to recent advancements in social networks, many people can consume diversified services on a daily basis and have developed an association with different communities of interest (COIs) via these services. However, a person only accesses a subset of these services at a given time either to consume certain services or to share information with a COI. This paper tries to answer two important research questions: 1) “how to dynamically capture user context from heterogeneous sources” and 2) “which services and COI are related to any given context.” To address these two challenges, we propose a framework called SenseFace, which provides user context from two sources: 1) a body sensor network (BSN) and 2) multimedia information contained the within social network space. We present the detailed design and implementation of the framework and share our preliminary test results.

M-IAR: Biologically Inspired Routing Protocol for Wireless Multimedia Sensor Networks

In this paper, we propose multimedia-enabled improved adaptive routing (M-IAR) that is optimized for single-source-to- single-destination multimedia sensory data traffic. It is an extension of the improved adaptive routing (IAR) algorithm presented in our earlier work, in response to the increasing number of applications incorporating wireless multimedia sensors such as wireless microphones and cameras. M-IAR is a swarm-intelligent- based algorithm exploiting the concept of ant colony optimization to optimize end-to-end delay, jitter, latency, energy consumption, packet survival rate, and routing path, within the multimedia wireless sensor network. The presented algorithm is proven to satisfy its goals through a series of computer simulations.

A framework for repurposing multimedia content

Nowadays, there are a lot of different device profiles (desktop PC, Web TV, handheld PDA, Internet screen telephones, cellular telephones, DTV and network computers, etc) for accessing online multimedia content. Developing appropriate multimedia content for each of the abovementioned devices that may also function in different networks is very expensive and somehow unmanageable. Content repurposing deals with this problem by taking multimedia content designed for a particular device or platform and automatically repurposing it to fit other platforms or devices. The basic idea is to maintain a single copy of the content in its original form and to separate the actual content from its presentation format. The approach proposed in this paper uses Web services technology to repurpose multimedia content to fit any desired device automatically. In our framework the multimedia content is stored in distributed databases and is described using metadata standards. Once the system receives a specific request, it compiles the response according to the user profile and end device. If a specific repurposing service is not available in the local system infrastructure (e.g., to transcode a tiff image into a png image), a Web services request is made to a specific UDDI server requesting an appropriate repurposing service. If a service is found we make use of its capabilities, otherwise we try to find a bridge to solve the request (e.g., transcoding tiff into jpg and then jpg into png). In this paper we describe the architecture of the system and its main functionality.

LORNAV: A Demo of a Virtual Reality Tool for Navigation and Authoring of Learning Object Repositories

Navigation in 3D world has reached its pinnacle with the advent of several technologies like JAVA, XML, WEB SERVICES, VRML, X3D etc. A lot of efforts have been given to visualize and navigate in virtual mall, cities, digital libraries etc. Most of them visualize only static objects. We designed a Virtual Reality (VR) Tool, called Learning Object Repository Navigation and Authoring in Virtual environment (LORNAV) that extracts Learning Object Metadata (LOM) dynamically from repositories and creates 3D representation of these objects. The proposed tool provides several facilities such as personalized navigation allowing a user to view content that is of interest to him. It also helps users to create new aggregated Learning Objects (LOs) from existing ones in a 3D Environment to be presented in SMIL format.

A PEER DATA SHARING SYSTEM COMBINING SCHEMA AND DATA LEVEL MAPPINGS

Peer data sharing systems use either schema-level or data-level mappings to resolve schema as well as data heterogeneity among data sources (peers). Schema-level mappings create structural relationships among different schemas. On the other hand, data-level mappings associate data values in two different sources. These two kinds of mappings are complementary to each other. However, existing peer database systems have been based solely on either one of these mappings. We believe that if both mappings are addressed simultaneously in a single framework, the resulting approach will enhance data sharing in a way such that we can overcome the limitations of the non-combined approaches. In this paper, we present a model of a peer database management system which allows a bi-level mapping that combines schema-level and data-level mappings into a single relational framework. We present the syntax and semantics of this new kind of mappings. Furthermore, we present an algorithm for query translation that uses the bi-level mappings. Our algorithm relies on tableau for expressing both queries and mappings.

Autonomous Dead-Reckoning Mobile Robot Navigation System With Intelligent Precision Calibration

An open hardware architecture for a goal-oriented indoor mobile robot navigation based on corrected odometry information using fuzzy logic controller is presented in this paper. The proposed approach exploits the ability of mobile robots to navigate in unstructured, cluttered and potentially hostile environments using calibrated odometry information, proximity sensor data and a fuzzy logic engine. A key advantage to this technique is its simplicity over similar navigation systems discussed in the literature. The simplification stems from the fact that only the previous traveled position of the robot needs to be tracked to reach to the target position. The superiority of this technique is supported by the experimental results that were collected for this purpose.

Ontology-Based Unification of MPEG-7 Semantic Descriptions

MPEG-7 provides a rich set of tools for describing multimedia content. Among them, the semantic descriptor scheme (DS) is used to describe the semantics of the content in terms of events, objects, concepts, places, time and abstraction. However, to describe similar facts presented in different multimedia contents, different semantic descriptions may result, even after following the MPEG-7 semantic DS. These semantic descriptions may be unified in order to enhance the overall knowledge about the associated multimedia content. This paper proposed an ontology that semantically represents the structure of MPEG-7 semantic DS and acts primarily as a resource of such unification. The knowledge representation provided by this ontology can be used to develop tools that perform automatic multimedia reasoning from different existing semantic descriptions, which are narrated with other domain specific ontologies.

MeTaMaF: Metadata Tagging and Mapping Framework for Managing Multimedia Content

Metadata comes into forefront as a savior of multimedia search and management. However, the existence of the diverse set of metadata standards and the different vocabularies used by these standards has made that task especially challenging in recent days. In this paper, we propose a framework for managing multimedia content by effectively dealing with the heterogeneous multimedia metadata in a transparent fashion. The cornerstone of our approach is to leverage the existing metadata standards and provide schema and data level mapping among them. The proposed framework also allows adding new tags/vocabularies with the given metadata vocabularies, defining equivalency relationship among those vocabularies, and separately managing the metadata vocabularies outside of the actual media files. We have developed a prototype of the framework and evaluated its performance in terms of some basic query execution times

Edge computing framework for enabling situation awareness in IoT based smart city

Abstract The Internet of Things (IoT) offers a lot of benefits for building smart cities. Such cities will be able to utilize a huge number of heterogeneous IoT devices that can generate a sheer volume of data. So, considering this heterogeneity, one of the major challenges in smart cities is how to process this data and identify different situations for decision-makers on the basis of this data. The traditional cloud computing approach can provide enormous computing and storage facilities to support data processing. However, it requires all the data to be moved to the cloud from the edge devices of the user endpoint, thus introducing a high latency. In this paper, we used the edge computing approach to minimize such latency. Besides, as major portion of data is generated from the user endpoint, processing this data in the edge can significantly improve the performance. Our experiment shows that processing raw IoT data at the edge devices is effective in terms of latency and provides situational awareness for the decision makers of smart city in a seamless fashion.

A P2P Sensor Framework for Collaborative Robots Manipulation

We propose an open hardware and software architecture for the cooperative coordination of multiple mobile robots operating in a common environment. It is designed to meet the stringent requirements of loosely coupled multi-robot architectures, such as flexibility, reliability, and fault-tolerance. As such, the proposed architecture enables the robots to deal with various types of uncertainties in their operating environments. The proposed architecture takes advantage of scalable sensory- based P2P framework. It also offers an inter-robot communication protocol, which is specifically designed to satisfy the requirements of physical sensory data publishing and fusion. The architecture is implemented and evaluated on a team of indoor mobile robots. The test results manifest the architectures distinguished features and capabilities.