5) Wise-IoT (Worldwide Interoperability for SEmantics IoT) (EU H2020)

Period: June 2016 - October 2020

Organization: Telecom SudParis, France

Designation: Research Engineer & PhD Candidate

Tools Used: Netbeans, Java, Tomcat, MySql, Postman


Developed an IoT Recommender for smart parking (in Santander, Spain) and smart skiing (in Chamrousse, France) use cases. In smart parking use case, IoT Recommender provides a nearest parking spot and least crowded route from user’s current location to the chosen parking spot by analyzing the traffic sensors deployed at Santander, Spain. In smart skiing use case, IoT Recommender provides ski routes which passes through slopes and ski lifts by modifying GraphHopper open source routing engine to implement routing for ski slopes and lifts.

Overview of WISE-IoT project:

While the Internet of Things is addressing a multiplicity of still-emerging standards and Alliance specifications with efforts to structure them into reference architectures, the Wise-IoT project gathers lead contributors from Europe and Korea to on-going major global IoT standardisation activities with the objective to strengthen and expand emerging IoT standards and reference implementation using feedback from user-centric and context-aware pilots.

Six testbeds from Europe and South Korea will be federated to implement smart city, leisure and healthcare pilots demonstrating GIoTS based applications roaming capabilities across continents. An iterative development approach is being implemented to allow requirement and architecture adjustments as well as alignment and contributions back to on-going standardisation activities through submissions in technical committees and interoperability events support. A strong plan for dissemination has been set-up and will have its peak during the trials to be run at PyeongChang Olympic and Paralympic Games (

4) Indoor positioning and navigation

Period: March 2015 - October 2015

Organization: Sunway University, Malaysia

Designation: Research Assistant

Tools Used: Android, Java, Android Studio


Today, indoor positioning, along with indoor navigation, is currently no longer impossible. Nevertheless, it is still an interesting and growing research area. The objective was to explore various techniques that enable unsupervised approach to learn and build patterns, commonly known as fingerprints, that may lead to usable, or better still precise indoor positioning. After successfully positioning a person in an indoor environment, indoor navigation was performed.

3) SMART: A Spectrum-Aware Cluster-based Routing Scheme for Cognitive Radio Networks

Period: August 2013 - February 2015

Organization: Sunway University, Malaysia and MIMOS Berhad, Malaysia

Designation: Research Assistant & MS Thesis

Tools Used: Network simulator QualNet, C/C++, Cygwin, Bash scripting, AWK scripting, LaTeX


To design and implement cluster-based routing scheme for cognitive radio networks. Its performance is evaluated by simulations using network simulator QualNet.

2) Direct Admit System for Hospital (DASH)

Period: November 2012 – May 2013

Organization: KNYSYS LLC

Designation: Software Developer

Tools Used: Web2Py, Python, HTML, CSS JavaScript, ExtJS, PostgreSQL

Description: is a healthcare tool that streamlines and significantly improves the hospital direct admission process. The goal is to swiftly admit patients from an out-patient setting into a hospital. DASH was designed to speed up the patient admission process and avoid wasting valuable time and money. To achieve this goal, DASH empowers healthcare givers and associated staff of the DASH-enabled hospital.

1) Think Realtime

Period: August 2012 – October 2012

Organization: KNYSYS LLC

Designation: Software Developer

Tools Used: ASP.NET, C#, HTML, CSS, JavaScript, JQuery, MS SQL server

Description: is involved in advertising, high-frequency stock trading and machine learning. It provides its clients an infinitely scalable, fully automated system that optimizes the purchase of Real-time Bidding (RTB) enabled banner inventory exclusively on the Google Display Network, thus maximizing online display advertising effectiveness.