Research Projects

Project Name : Video Recommendations

Project Overview :

Recommendations of existing videos of different faculty’s lectures; YouTube video lectures recommendations for courses and subtopics video lectures.

Description :

The module generates recommendations according to lecture topics from YouTube using Machine Learning Algorithm. According to lecture topics, links of existing videos of faculties are displaying. Also related topics and subtopics videos, which are available on YouTube are also recommending. User needs to enter the topic keyword and module will find and show results using the machine learning algorithm. By the time, the module will be more and more accurate for giving suggestions.

Project Name : Video Indexing & Recommendations

Project Overview :

In this new age of technology, everything works on digital platform like web or mobile education and learning apps.

  • Model will provide topic indexing based on keywords present into video so that a learner can directly view and understand a particular topic.
  • Model will also provide more video recommendation based on keyword present into video. YouTube video analytics generate word cloud, index of content.

Description :

New technology era is highly influenced by mobile apps and web modules. People prefer using mobile apps and internet based applications widely. This Video Indexing & Recommendations module is provided on website as well as mobile app for general group of users. The module will provide video recommendations based on highest referred keywords and according videos. The learner will be able to get the most frequent topics videos. Also more relevant videos according to keywords present in the video links will be suggested. The analytics module of the project will generate the most frequent referred keywords cloud and its index to ease of interpretation for recommendation.

Project Name : Image based Attendance Taking System

Project Overview :

Filling attendance sheet in large size classroom or training session end up with some kind of issues like consumptions, man made errors, cheatings or frauds.

With the use of Image based attendance taking system, an instructor or admin staff can get rid of such issues.

  • The module will provide a facial recognition system to identify an admitted person (student) from clicked classroom photograph or CCTV footage.
  • As and when the person is identified and recognized, the module will make the present of the student.
  • The module will be deployed on cloud server to automate the system.
  • As the end result, instructor or admin will get the final report of attendance which would be stored in server DB.

Description :

The time of manual work has gone in latest technical era. To minimize error level and to get maximum accurate result along with lesser human efforts, the Image matching based Attendance taking System is proposed and developed. There are chances of cheating or fraud, human made errors, time consumption, for larger classroom or huge student crowd.

The module of Facial matching based Attendance System used Image Recognition Algorithm to match the Faces of students along with registered student images. The CCTV or Classroom photograph of students is used to get the present students of relative lectures. Identified and Recognized images of the student will make the present automatically in the module.

Users of the system will be faculty member and administrator of the system along with the according user credentials.

Project Name : Lead Management & Tracking CRM

Project Overview :

An organization has different channels which generate traffic like social media platform, Company website and many more. The data would be stored somewhere in database.

The model is developed to get insights from the data dump so it can be converted as many as leads needed. Each lead is rated on 5 scales. The model is developed to:

  • Find out the probability of application & admission.
  • Build dashboard for source of enquires from different channels like facebook, google, email…etc.

Project Name : Identifying Customers and Customize Marketing

Project Overview :

In any organization, certain amount of capital invests on marketing and sometimes it doesn’t provide fruitful results. So based on historical data and already present identifiers in it, a sale or market can be targeted on a group of person for a kind of marketing. This can provide growth to the organization and better resource utilization.

  • An analytical module which will provide different clusters of same kind of customers.
  • Identifying or predict what kind of information can be share by next time.

Project Name : Lead Distribution within Team and Performance Matrix of Employees

Project Overview :

Any organization has different channels which generate traffic like social media platform, company’s own website and many more. For distribution of these leads within the team based on experience of employees and level of urgency is separate task.

  • Every day model will distribute the leads evenly based on employee available into team. So that company gets proper coverage into leads and gets benefits from investment over various social media channels.
  • Module will also find out productivity of individuals.

Project Name : Face Login on mUniversity Account

Project Overview :

mUniversity is a learning and management platform where a registered learner can Login and use the platform to enhance his / her skills. For the mUniversity admin team provides Login and password to a registered participants or student, which can be sharable with anyone to use further.

  • The module will provide a second level of security to the platform and reduce the frauds.
  • Based on facial features of the person (who will try to Login), it will detect and recognized only registered person and provide him / her access.

Description :

Text based passwords now days can be big reason to create frauds on the online platforms like mUniversity. So the solution is to eliminate password based authentication and include the unique features like Facial or Biometric based Authentication. There are lesser chances of password leakage of facial or biometric based features for online platforms. Facial features always vary from person to person. The module provides a second stage of security on the online platform. The registered users of the mUniversity platform will only be able to Login to the online portal and the captured image of the user will be matched to the registered one.