- Description
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PathoScan is a startup focused on revolutionizing agricultural practices with its innovative crop disease detection device. By allowing on-site and immediate identification of diseases, the device eliminates the need for centralized lab facilities and the associated delays. This transformative approach not only reduces costs but also empowers farmers with timely decision-making tools to ensure optimal crop health.
- Number of employees
- 2 - 10 employees
- Company website
- https://pathoscan.com
- Industries
- Agriculture
Recent projects
HumeTerra Fertilizer Effectiveness Validation
This project entails two possibilities for students. HumeTerra Testing: PathoScan and HumeTerra have partnered to validate the effectiveness of their latest fertilizer. In this project, students will work with the CTO of HumeTerra to develop an experimental plan. They will then execute this experimental plan and collect results using Polymerase Chain Reaction and Nanopore ITS sequencing. Finally, the student will return a report to HumeTerra detailing their results. PathoBox Assembly: The PathoBox is PathoScan's flagship product. In this role, the learner will learn to assemble the PathoBox. They will then analyze the assembly process and give feedback on how the process can be optimized.
PathoBox Enhancement and Production
PathoScan Technologies Inc. is seeking to enhance its existing PathoBox device by integrating a speaker system and SYBR capabilities. The PathoBox is a portable diagnostic tool used in field settings, and these improvements aim to increase its functionality and user-friendliness. The addition of a speaker will enable audio alerts and instructions, enhancing user interaction. Incorporating SYBR capabilities will expand the device's diagnostic range, allowing for more comprehensive field testing. The project involves designing and implementing these enhancements while ensuring the device remains compact and efficient. Additionally, the project includes the production of a batch of PathoBoxes for the upcoming field season, ensuring they meet quality standards and are ready for deployment.
Pathoscan Field Trial Success
The goal of this project is to ensure that Pathoscan can have a successful 2025 field trail by optimizing our Pathobox production process using hands-on experience. It is ideal for teams of learners participating in an interdisciplinary studies such as InterD or Global Challenges classes. This will allow students to learn how point of collection testing works from a holistic perspective. There will be two members of the team: Laboratory Manager: The laboratory manager will be responsible for processing the outstanding samples delivered by our clients under the direction and supervision of Proxima R&D. In this role, the student will have hands on experience with our partners at Proxima R&D laboratories in microbial techniques including PCR and qPCR. These samples are not mission critical, and are intended to serve as a quality control mechanism that the Pathobox Manager will use to ensure that the Pathobox is functional. Pathobox Manager: In this experience, the student will learn how to assemble electronics components with hands-on experience so that they can optimize the assembly process of the Pathobox. If interested, the student can also learn how to use FDM manufacturing technologies.
AI Enhancement for PathoBox
PathoScan Technologies Inc. aims to enhance the AI capabilities of its flagship product, the PathoBox, a device designed to assist in the rapid analysis of pathological data. The current AI functionality, while effective, requires optimization to improve accuracy and processing speed. The project involves analyzing the existing AI algorithms, identifying areas for improvement, and implementing enhancements. Learners will apply their knowledge of machine learning and data analysis to refine the AI models, ensuring they are robust and efficient. The goal is to achieve a more responsive and precise AI system that can better support healthcare professionals in diagnosing and analyzing pathological samples. This project provides an opportunity for learners to engage with real-world AI applications in the healthcare industry.