Bacterial Colony Classifier
The problem is that Bacterial colony classification process requires several biochemical tests, sequencing methods, expert human knowledge, and experience to ensure that observed test results are accurate and the identified bacterial colony belongs to the desired species. The rec
2025-06-28 16:30:35 - Adil Khan
Bacterial Colony Classifier
Project Area of Specialization Artificial IntelligenceProject SummaryThe problem is that Bacterial colony classification process requires several biochemical tests, sequencing methods, expert human knowledge, and experience to ensure that observed test results are accurate and the identified bacterial colony belongs to the desired species. The recognition of the bacteria species based on the shape of the bacteria and their colonies is challenging even for experienced specialists and may require additional analysis with the other microbiological characteristics because species of bacteria are morphologically diverse and share very similar shapes and sizes.
Affects Microbiologists, Researchers, Doctors and Students and Healthcare Industrialists who need to classify bacteria for various purposes. Impact of which is Lengthy manual process, experienced specialists and extensive resources are required for bacterial colony classification which is prone to human error.
A successful solution is eliminating the need for manual testing, specialists, high-end equipment, as well as reducing time and cost by automating the classification of the bacterial colony using Image processing and Deep Learning techniques.
The system will provide a platform to instantly
- classify bacterial colony images
- generate reports from processed results
- maintain results in an orderly fashion.
This project enhances the existing identification process of a bacterial colony. This is accomplished by eradicating the need for manual testing, specialists, high-end equipment, as well as reducing time and cost by automating the classification of the bacterial colony using Image processing and Deep Learning techniques.
The proposed system will provide a platform to instantly classify bacterial colony images, generate reports from processed results, and maintain results in an orderly fashion.
Classification of bacteria will be revolutionized throughout Pakistan, creating awareness of Deep Learning, Artificial Intelligence and Image Processing and how these domains can help increase the productivity in the healthcare industry.
From our persepective, learning new tools and technologies in the field of Artificial Intelligence, Image Processing and Mobile Application development with Cloud services is our personal objective to accomplish via developing this application.
Project Implementation MethodThe implementation phase requires to explore and research on Machine Learning/Deep Learning Algorithms, gathering dataset, Image Processing techniques.
Implementation will be done using React-Native to develop the interface for both types of mobile platforms. This front-end will need a storage for user credentials and results. For this, Firebase (Third-Party) storage will be used. The maintainablity, efficiency and reliability will not be compromised in this regard.
Finally the backend needs to be conducted in python which will be deployed using cloud services so that reliabilty and efficiency is not an issue.
Benefits of the ProjectA research based application that will modify this approach and make it easier, faster, and precise to identify the genera and specie to which a given bacterial colony belongs without the need to have advanced biological testing and human effort, thus cutting down time by a great margin. The instant identification of bacteria will allow research and cures to advance further than their current speed which will revolutionize the work ethic of researchers and Microbiologists where they can conveniently identify bacteria and get formatted results by simply plugging the microscopic image of bacterial.
The extreme outbreaks of epidemic diseases will be easier to locate and eradicate. This is serious health issue will have yet another help in locating bacteria and therefore less efforts and resources will be needed to locate and identify and more focus will be to cure these microorganisms and the disaster they spread.
Personal gains are another bonus that will stay with us forever. In addition, industry will move towards automating difficult tasks.
Technical Details of Final DeliverableThe final product will be a native application for both iOS and Android users. This application will provide Deep Learning, Image Processing and database backend storage for user data on Firebase. The users will be submitting a microscopic image to the application either via a microscopic camera or from thier gallery. This image will then be classified into known classes of Bacterial species. The results provided from the application will then be used to organize in a logical manner within the application. From these organized results reports will be generated to aid users to further present their findings without the need to handwrite the results all over again.
The challenges to face are the research aspects along with the learning of new languages such as React-Native and its integration with cloud services.
The final product will be available for Android (Lollipop 5.0 and above) and iOS (10.0 and above)
Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Medical , Health Core Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 42000 | |||
| Microscopic Camera | Equipment | 2 | 16500 | 33000 |
| iOS-App Store Account Creation | Miscellaneous | 1 | 9000 | 9000 |
| Stationary (Printing) | Miscellaneous | 0 | 1000 | 0 |