Real-Time Transcription & Translation API Development

Innovate Landfill Solution Canada seeks to enhance its existing Node.js API to support real-time transcription and translation services at scale. The current system, which may have a basic Node.js setup, requires significant improvements to manage incoming audio uploads, session data, and integration with external APIs such as Google Cloud Translation and future GPT models. The goal is to develop a well-structured, secure, and scalable backend that efficiently handles real-time data flows and integrates seamlessly with cloud resources. This project will provide learners with the opportunity to apply their knowledge of Node.js, cloud services, and API development to create a robust solution that meets the company's needs. The project will focus on optimizing performance, ensuring data security, and enabling seamless integration with external services.

Optimizing Sales Strategy for RE-CUP

Innovate Landfill Solution Canada is seeking to enhance its sales strategy and revenue model for its innovative waste management solution, RE-CUP. The project aims to analyze current market trends and develop a comprehensive plan to optimize pricing, sales channels, and customer acquisition strategies. By leveraging classroom knowledge in business and sales, learners will focus on crafting a market-ready strategy that aligns with sustainable growth objectives. The project involves researching competitor strategies, identifying potential customer segments, and evaluating the effectiveness of current sales tactics. The ultimate goal is to refine the sales approach to increase market penetration and revenue generation for RE-CUP.

Lixor WebApp Front-End Development: Real-Time Transcription & Translation UI

Innovate Landfill Solution Canada is seeking to enhance the user experience of their Lixor WebApp by developing a sophisticated front-end interface for real-time transcription and translation. The goal is to create a seamless and intuitive user interface that allows instructors and students to capture and display live transcripts in multiple languages. The project will involve designing an interface for session management, enabling users to start and stop recordings and manage multiple language windows efficiently. The front-end must integrate smoothly with the existing Node.js/Express backend via REST APIs or WebSocket to ensure low-latency updates. This project provides an opportunity for learners to apply their classroom knowledge of front-end engineering, focusing on implementing the final UI/UX design and ensuring a smooth data flow between the web front end and the backend.

AI-Powered Roof Damage Classifier MVP Development

The project focuses on developing a Minimum Viable Product (MVP) for an AI system designed to identify various types of roof damage, such as cracks, missing shingles, algae/moss growth, and hail impact. Innovate Landfill Solution Canada aims to streamline the roof inspection process by leveraging AI technology. The team will engage in user research to understand the needs of inspection teams and homeowners, ensuring the AI system is user-friendly and effective. Product documentation will be created to outline the AI's functionality, data requirements, and user interaction. Feature prioritization will be conducted to determine the most critical aspects of the AI system for initial development. The ultimate goal is to deliver a comprehensive requirements document that guides the development of the AI-powered roof damage classifier.