Effective Project Management - Casestudy
Tags: machinelearning, projectmanagement, facarecognition
Published: 2020-06-09 05:12:24

Overview

Practically, most construction companies would want their projects to be completed and delivered on time without any delay. It is the duty of a project manager to take proactive steps in order to avoid any hold ups.

But how can the manager get a hold of what is happening without getting an in-depth knowledge on the progress of work?

With the help of the project management tool, one can monitor the physical progress, manpower, labor productivity engineering, design status and direct cost. It assists the project team to monitor the 
physical progress through Daily Progress Reports and financial progress through Cost Register Reports.

The tool identifies and assesses critical areas of each project and based on its inbuilt alert system, slippages are monitored and hierarchically escalated to various stakeholders for effective decision making and taking necessary actions.

User can download the jobs that are related to them and update their progress both online and offline.

With the help of Machine Learning, attendance can be marked by the facial recognition of employees.

The facial feature matching technology helps the application user to match the faces of the employee with the database and provide exact match.

While marking attendance, with the help of facial recognition using Machine Learning, the system will be able identify and recognize any new faces and prompts the user to create a profile for them and add it to the existing labor list.

With the assistance of AI&ML, the system will be able to identify the faces of individual laborers and match it with the database, even if it has to run a facial recognition on a group picture.

Approvals

Superiors can approve a work progress entry in a particular location by just tapping on the pin location and the list of jobs that needs approval will be listed.

Tech Stack

Xamarin Forms: Xamarin.Forms is an open source cross-platform framework from Microsoft, that extends the .NET developer platform with tools and libraries for building mobile apps.

Zetetic-SQLITE: SQLCipher is a security extension to the SQLite database platform that facilitates the creation of encrypted databases.

OpenCV: OpenCV (Open Source Computer Vision) is a library of programming function mainly aimed at real-time computer vision. It is a library that is mainly used to do all the operation related to Image processing and Video analysis, as in the case of facial recognition and detection.

Cosine Similarity: Cosine similarity is a Similarity Function that is often used in Information Retrieval. It measures the angle between two vectors and in this case, used for facial feature matching.

TensorFlow: It is a framework developed and written in Python, C++ and Cuda. TensorFlow provides multiple API’s in Python, C++, Java etc. CNN architecture with TensorFlow backend has been used to extract vector facial features, which is the architecture behind computer vision applications.

Conclusion:

With the help of this management tool, delivering a project on time can be achieved by identifying and highlighting activities that are likely to cause delay and address the issues on time.

This tool also facilitates forecasting the manpower requirement based on quantum of works planned with respect to actual productivity reflected in Productivity Register Report.