Funded Projects

Funded Projects



S.No# Project Title Project Amount (Rs) Year of Completion
1
Video Surveillance Lab

Project Leader  :   Dr. Atif Tahir
Department    :   Computer Science
Funding Agency   :   NCBC, HEC


The laboratory aims to extract appropriate and timely information from video streams and build deployable models that can benefit government agencies, hospitals, and educational institutes. In this regard, the lab is currently working on multiple surveillance-based applications, namely but not limited to:
(a) Theft Car Surveillance
(b) Real-Time Weapon and Face Recognition
(c)Suspicious Activity and Evidence Detection using smart IoT systems and Active Learning, to address the needs of providing security to the citizens of Pakistan.

39,287,000

-

2
An AI Based Adaptive Framework for personalized e learning

Project Leader  :  Dr Jawwad Shamsi
Department    :  Computer Science
Funding Agency   :  NCAI


This research aims to propose an AI based personalized e-learning content recommendation framework which can be used to create an adaptive and adaptable learning system that caters to both in school and out of school children, empowering them to carry out self-paced learning and attain primary grade literacy. Adaptiveness will be achieved by assessing the level of each student and providing appropriate content, whereas adaptability will be incorporated through cognitive behavior and personal preferences and capabilities through the use of machine learning and deep learning-based AI approaches. This AI based content recommendation framework will be integrated in MUSE Learning Application from the industrial partner SABAQ in order to incorporate and enhance the decision-making capabilities in the system for the provision of tailored content to each user.

12,915,000

-

3
The efficient communication infrastructure for smart cities

Project Leader  :  Dr Jawwad Shamsi
Department    :  Computer Science
Funding Agency   :  NRPU


The smart city consists of a large number of loT devices, which are being placed for measurements and sensing. The sensed data is aggregated and sent to a cloud which make operational decisions to support and manage city services. In the coming years, it is expected that smart cities will play a major role in meeting growing challenges of population growth and urbanization. As large number of loT devices emit data, an efficient networking framework is needed to support large scale communication. Challenges include high speed switching, protection of cloud against attacks, aggregation of data, and proper validation and verification of messages emitting from loT devices. A robust mechanism is needed to meet these challenges effectively. Our proposed research has three major modules which are being developed for this purpose. The firewall and switching module will be used for efficient processing of large-scale loT messages, wheeras, thecomputaional module will be used for processing loT data and computation of results. The third module, will be responsible for effective validation and verificaiton of loT data. Together the three modules will be responsible for providing efficient network processing for lo Ts. The project is motivated to utilize high computational power of GPUs. Through this end, NVIDIA based research also be utilized in this project.

The project's cruicial objectives are :
  1. To develop an efficient network switching and routing infrastructure in order to support high speed networking for a large number of loT devices in a smart city. The framework must also possess capable firewall for protection of cloud against network attacks.
  2. To develop a middleware for big data processing for a large number of IOT devices in a smart city.
  3. To develop an efficient network for message validation and verifcation for IOT devices.

5,638,448

2021

4
Monitoring and Prediction of Chick's Health in Poultry Farms

Project Leader  :   Dr Ghufran Ahmed
Department    :   Computer Science
Funding Agency   :   Faculty Research Support Program FAST-NUCES


The project aims to monitor the health of chicks in a poultry farm. On the basis of movement of the chick in a day, its health status is being determined.The data is also used for prediction of disease in a chick who can be separated from his batch, thus spreading of disease is being avoided. The solution also incorporates real time monitoring of water through Internet of Things (IoT), being given to chicks as poor quality water is a major cause of poor health of a chick.These steps will result in improvement of production as well. Internet of Things (IoT) Based Poultry farming can play a major role in achieving the desired goals which a businessman is looking for. This project provides a low cost solution to the problems faced by local poultry farmers.

540,000

-

5
NVIDIA Teaching and Research Center grant

Project Leader  :   Dr Jawwad Shamsi
Department    :   Computer Science
Funding Agency   :   NVIDIA


In 2014, FAST-NUCES was selected as an NVIDIA Teaching and Research Center. The award recognizes FAST-NUCES to develop high performance computing based solutions for various projects such as computer vision, security, and network performance.

2,000,000

2016

6
Block Chain and Health Applications

Project Leader  :   Dr Jawwad Shamsi
Department    :   Computer Science
Funding Agency   :   National Grassroot IGNITE ICT R&D


Privacy is recognized as a basic human right by the United Nations in the Universal Declaration of Human Rights (UDHR) at the 1948 United Nations General Assembly. The aim of Patient-Centric Healthcare system using Blockchain technology is to ensure patient agency with respect to the patient’s personal health information. Consistent with GDPR standards, using Blockchain technology, we can develop a system (with Easy-to-use Interface) in compliance with HIPAA and HL7 standards of personal privacy. Once the data is accessible, epidemics analytics can be performed on the health data to predict patterns of certain diseases and infections prevalent in a particular area. Furthermore, interoperability among various Healthcare Organizations for better quality and availability of data is a concern that is possible using this project.

70,000

2020

7
VSAFE

Project Leader  :   Mr. Muhammad Danish Khan
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


Our project is VSAFE (Vehicular Safety System) which is based on VANETS. In VANETS, each vehicle act as a node. We are simulating the highway scenario on which the driver gets to know about the road conditions through the android application. The functionality of the system is in a way that there are sensors present in the environment that senses the environment and transmits data to Road Side Units(RSUs) and further that RSUs sends the data to the On Board Units(OBUs) present in the vehicles. OBUs further send that data to the android application through bluetooth. This simulation is done on NS3 simulator. It is totally based on Vehicle to Infrastructure Communication(V2I). The android application will get that data and generate alerts in order to notify the driver about the road conditions like road accident, traffic jam, weather conditions etc. The application is able to process the simulation trace files and based on the simulation data, it will give the results. The sensors that we are using are of humidity, temperature, sound and pressure.

70,000

2020

8
Smart Exam Surveillance System

Project Leader  :   Dr. Jawwad A. Shamsi
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


Smart Exam Surveillance System is not just a project it’s a solution to a problem in our society. The problem of using unfair means in an examination. This is basically an automation to the work of an invigilator in an examination hall but with better accuracy. Exam surveillance system involves 3 major task including Cheating detection in real time once any malicious activity is detected the next job of the system is to identify the individual that has been caught doing that malicious activity in the examination hall. And lastly the system would automatically interpret the entire scene and alert the management regarding the activity with recorded video streams through a web portal as evidence of the act. As much as the technology is growing providing better tools and technology for high accuracy there still always exists a possibility of an error hence in order to tackle this possibility the exam surveillance system includes a review System so that students get the right to defend themself. To address the major challenge of the project of Human Action Recognition at real time YOLOV3 is being used furthermore We have used pre tested FaceNet Algorithm for face recognition, whereas for web portal Flask framework is used.

70,000

2020

9
Patient Centric Health Care using Block Chain with Epidemic Analysis

Project Leader  :   Dr. Jawwad A. Shamsi
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


Privacy is recognized as a basic human right by the United Nations in the Universal Declaration of Human Rights (UDHR) at the 1948 United Nations General Assembly. The aim of Patient-Centric Healthcare system using Blockchain technology is to ensure patient agency with respect to the patient’s personal health information. Consistent with GDPR standards, using Blockchain technology, we can develop a system (with Easy-to-use Interface) in compliance with HIPAA and HL7 standards of personal privacy. Once the data is accessible, epidemics analytics can be performed on the health data to predict patterns of certain diseases and infections prevalent in a particular area. Furthermore, interoperability among various Healthcare Organizations for better quality and availability of data is a concern that is possible using this project.

70,000

2020

10
Learning Imbalanced Data using Differentiate deregularization of the Loss Function

Project Leader  :   Dr. Tahir Syed
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


The class imbalance problem is common in most real-world machine learning problems. Generally, it is mitigated using sampling methods, classifier ensembles or cost-sensitive learning. In this work, we propose a novel loss function, the Focused Anchors Loss, by combining cost-sensitive learning with discriminative feature learning. We evaluate our loss function on 6 highly-imbalanced datasets and the experiments show that the proposed loss function and its variants consistently outperform cross-entropy loss and focal loss, and produces comparable or better results to sampling methods without having to incur the extra computational cost associated with those methods.

70,000

2019

11
Six Axis articulated Robotic Arm for Industrial Applications

Project Leader  :   Engr. Muhammad Ahsan Khan
Department    :   EE Department
Funding Agency   :  National Grassroot IGNITE ICT R&D


Human body can be considered a very complex machine which is a perfect combination of joints that have the ability to reach maximum degree of movement. Technology is advancing on an unprecedented rate and robots have even replaced humans in countless fields including linguistics, engineering, medicine etc. This revolution is in part to the incredible accuracy and countless man hours that robots can engage for, especially when compared to humans. The shortcoming of machines is that they are restricted to specific tasks and lack the dynamic skills that a human does. Our objective is to create one such robust machine, capable of multiple tasks, resembling the work and adaptability of a human. Furthermore, we aim to exceed the limitations of a human hand and produce results that would be otherwise unattainable by a human. However, as our basis, our project derives its improvements by observing the mechanics and working of the human body.

70,000

2019

12
Home Automation using hololens

Project Leader  :   Dr. Jawwad A. Shamsi
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


The project is based on the basic concept of Home Automation implemented using emerging technology HoloLens. Normal home appliances, such as televisions, refrigerators, fans, lights, and many others have a physical mechanical switch to turn them on/off. However, our motivation is to replace those switches with augmented 3D switches. HoloLens has unique gesture-based I/O features that will help in interacting with the physical home appliances. HoloLens was connected with the Raspberry Pi via Internet, using Azure IoT Hub. Azure IoT Hub is a medium between both devices to exchange messages. Two Universal Windows Platform (UWP) applications were developed; one was developed for HoloLens and the other for Raspberry Pi. The Raspberry Pi is the brain which will make simple home appliances smart. We connected the bulb with the Raspberry Pi via a 4-Channel Relay and then sent a turn on/off signal to the Raspberry Pi by tapping on the virtual/augmented button visible beside an electronic device. Whenever we tapped on the button, the UWP application running on the HoloLens forwarded and stored the corresponding command at the Microsoft Azure IoT Hub and then the command sent to the connected devices at IoT Hub. Raspberry Pi supplied voltage on the basis of command turn on/off (min is 0 and max is 5). If the command received is “ON”, the bulb was successfully turned on and if the command received is “OFF”, bulb was successfully turned off.

70,000

2019

13
Rapid Detection of Crime Using Deep Learning on Fog Nodes

Project Leader  :   Dr. Jawwad A. Shamsi
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


Due to the rapid urbanization, cities are converting into smart cities. Safety is an essential requirement in a smart city and the performance of the currently available surveillance systems is not real time. To solve the above mentioned problem, we propose a rapid crime detection surveillance system using fog nodes that can detect crime and take appropriate actions in real time. We propose an architecture based on fog nodes that will distribute the data constantly coming from video streams and provide storage, reduced latency, and improved processing. Although fog nodes speed up the processing, we still need a fast object detection algorithm and face recognition system that can detect criminal artifacts and criminals respectively in real time. Therefore, the robust and the most accurate object detector available to date is selected. Experiments of retraining YOLO were performed on different dataset sizes and achieved an mAP of 0.85 on Openimage test and validation set combined with Coco person dataset. We also transferred data between the fog nodes using infini band for our proposed architecture and it provides a significant reduction in transfer time between fog nodes.

70,000

2019

14
The Eye Stick Walking Stick that sees

Project Leader  :   Dr. Zulfiqar Ali Memon
Department    :   Computer System
Funding Agency   :  National Grassroot IGNITE ICT R&D


According to the US Census Bureau Report 2012, 56.7 million people in this world which is almost 19% of the world’s population, are suffering from some sort of physical impairment that affects their daily life. This 19% population of the world requires some sort of external support to perform the daily chores of their life. As the technology has progressed, various companies, such as Google, Indiegogo, and Microsoft have produced few assistive gadgets, some of them are Google Glass and WeWalk to create an impact, but these tools and instruments are quite costly for the majority of the affected class. Over 3 billion people in this world are living a life of poverty and cannot afford the apparatus that eases their lives. The purpose of this project is to produce a prototype of a cost effective and affordable solution for the people who face troubles due to some sort of physical disability. The Eye Stick with an infra-red, pressure, and moisture sensor along with a camera together with bluetooth connectivity with a back end neural network engine is being developed considering the latest technological trends and social requirements. Currently the hardware device with embedded sensors is functional. An object classification module that classifies few basic objects is also to be embedded in the final product to assist the person in navigating through the paths. The most advanced feature planned for this is real time image processing with voice command recognition. 65% of the product is ready, but rigorous testing of features is required considering the real world environment.

69,540

2019

15
Formation Control of Multiple UAVs

Project Leader  :   Engr. Muhammad Haris Mohsin
Department    :   EE Department
Funding Agency   :  National Grassroot IGNITE ICT R&D


Formation control techniques are burgeoning vis-a-vis other operations involving single UAV. This can be credited to the wide array of applications involved with the use of multiple UAVs for a task rather than a single. The swarming technique for the coordinated control of UAVs. The Matrix decomposition method is used in this regards and appropriate gain values are assigned to the eigenvector in order to keep the UAVs in a trouble-free and well-ordered formation. The communication topology applied is straightforward where both drones are assigned with different frequencies in order to avoid any communication losses that the UAV may encounter if assigned with the same frequency value. The hardware prototype involves two drones one of which is designated as a master while the other one is designated as the slave. The UAV is programmed in python and the controller used in Ardu Pilot Mega 2.8. Four brush-less carbon motors are used that are mounted on the end of the X-frame. Two telemetries of different frequencies are used. The frequency of 415 MHz is assigned to the master drone whereas the frequency of 915 MHz is assigned to slave drone. The telemetry basically has two modules i.e. Air module and Ground Module. The air modules of both telemetries are mounted onto their respective UAVs. The master drone sends the command to the ground station setup that is linked to the IDE Mission Planner. The ground stations of both drones are synchronized and hence the command is sent to the air module of slave drone via ground station.

58,550

2019

16
Automaid The Smart Vacuum

Project Leader  :   Engr. Dr. Syed Muhammad Atif Saleem
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


Robotics is a growing field of interest in today's world, where most of the researchers are paying attention on using robots to give mankind a comfortable life. The essence of this project lies in a similar idea that is to clean cotton fluff/dust using an automated robot cleaner, Automaid. The key features of the machine include cleaning in autonomous mode and in manual mode via mobile application. Self-tracking using either the SLAM algorithm or OpenCV edge detection and self-charging functions using either of the aforementioned technologies would make this product standout in the market and meet the needs of customers from industries to homes.

55,190

2020

17
Sentimentos

Project Leader  :  Mr. Zeshan Khan
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


In today’s world, with increasing approach in technology, various music players have been developed having different advanced features i.e. fast forward, shuffling, speed controls, variable play back and playback with multi cast stream. These features fulfill the basic requirements of the user but still user needs to search and browse the music to listen according to the user’s mood. As one usually listens to music according to his or her mood and behavior. The introduction of emotion based music player in the traditional music applications will omit the mess of the searching and browsing the music according to the current mood instead it will automatically present a playlist of the related songs by identifying the emotions of the user.

55,000

2020

18
Ensemble of Deep Learning and Local features for Robbery Detection

Project Leader  :   Dr. Muhammad Atif Tahir
Department    :   Computer System
Funding Agency   :  National Grassroot IGNITE ICT R&D


In our daily lives, we all witness or hear about robberies every other day, but rarely do we hear that the law enforcement officials were notified during the time of the act and/or they stopped it. It is only after the robber has robbed and left the place that the personnel are free to move and alert the local law enforcements. CCTV camera, however, watches and usually records the entire act. Usually, there is a person who is monitoring the CCTV feed which can then detect the robbery. Nevertheless, this method is not only expensive but can fail due to human error. For example, the guard can fall asleep, go for a break, be bribed, or even get hurt by the robbers. Our project aims to automate this process by detecting robbery using just the CCTV video feed as input. Frames are extracted from the input video and are processed in our detection module which is build using a combination of three techniques of computer vision and image processing, which then provide an output in the form of a binary classification of whether there is robbery or not.

45,000

2019

19
Autonomous UAV based power line inspection

Project Leader  :   Engr. Dr. Syed Muhammad Atif Saleem
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


This project represents a smart building (office) management system which is designed for human ease, is the important concept in order to achieve monitoring and controlling. The office automation system can be controlled through personal smart phone. A mobile app will be developed which provides interface to control systems. The systems such as smart lighting, HVAC systems, security and water management etc. This method makes comfortable and easy access to particular appliances from smart phone. A solar plant is installed for this building. Monitoring of solar plant generation, voltage and load is done to ensure the energy efficient environment.

44,470

2020

20
Gravity Assisted Energy Storage System

Project Leader  :   Engr. Dr. Syed Muhammad Atif Saleem
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


GAESS is an innovative idea to store the excess energy from Renewable sources such as Solar and Wind at times of over-generation which occurs during off- peak hours in order to accommodate the load demand during Peak hours. Usually at times of over-generation the suppliers curtail the renewable sources purposely as their base load is maintained by their primary generators. This voluntary cut-off of sources can be viewed as a loss as investments for Renewable plants have been made which are not being used to their full potential. This problem can be solved e ffectively and efficiently if there was a way to store the excess energy rather than allowing it to be wasted. GAESS provides a worthwhile solution to the problem as energy can be stored for later uses. This reduces the problem of load mismanagement during peak hours.

42,780

2020

21
AUV Autonomous Underwater

Project Leader  :   Engr. Syed Asim Mehmood
Department    :   EE Department
Funding Agency   :  National Grassroot IGNITE ICT R&D


In this project, the problem of tracking an Autonomous Underwater Vehicle is discussed. The main idea is to interface the hardware with the simulated results. The controller is designed in three planes namely Yaw, Pitch and Depth. PID is used as the control scheme for trajectory tracking. This paper suggests solution particularly to the problems of controlling the heading of AUV in a horizontal and stern plane. The simulation result has been shown to prove the performance of the controller. Based on the simulation result, we designed hardware for the experimental purpose to solve the practical problems like monitoring and rescue operations.

42,160

2019

22
Smart Green Building

Project Leader  :   Mr. Muhammad Danish Khan
Department    :   Computer Science
Funding Agency   :  National Grassroot IGNITE ICT R&D


This project represents a smart building (office) management system which is designed for human ease, is the important concept in order to achieve monitoring and controlling. The office automation system can be controlled through personal smart phone. A mobile app will be developed which provides interface to control systems. The systems such as smart lighting, HVAC systems, security and water management etc. This method makes comfortable and easy access to particular appliances from smart phone. A solar plant is installed for this building. Monitoring of solar plant generation, voltage and load is done to ensure the energy efficient environment.

34,640

2020

23
Atmospheric Water Generator

Project Leader  :  Engr. Syed Asim Mehmood
Department    :   EE Department
Funding Agency   :  National Grassroot IGNITE ICT R&D


About a billion of people around the globe are affected due to scarcity of water. According to the research it is found that the areas that are water scarce are mostly the regions near the coast even having the sea nearby, there is shortage of drinkable water. The desalinization is a solution to this problem in such areas. This is not a cheap method to extract water and fulfill the needs. The proposed method is the cheap solution to this water related problem. The atmospheric water generator requires the humid air to extract water out of it that is sufficiently available in the coastal regions making it a good source of obtaining water.

24,110

2019