Data Framework for LED Optimization in Greenhouses and Vertical Farming
Lumesmart Inc. seeks to enhance its LED lighting solutions by leveraging AI to simulate performance across diverse greenhouse and vertical farming environments. The goal of this project is to design a comprehensive data collection and analysis framework that will serve as the foundational training input for an AI tool. This AI tool will be capable of simulating how different LED lighting solutions perform under various agronomic and operational conditions, ultimately generating ROI-focused recommendations for growers. Students will be tasked with identifying key data points necessary for accurate and actionable AI simulations. These data points may include environmental factors, crop types, growth stages, and energy consumption metrics. By applying classroom knowledge in data analysis and AI, students will contribute to creating a robust framework that supports Lumesmart Inc.'s mission to optimize LED lighting solutions for sustainable agriculture. Key Responsibilities Identify and document key data inputs (e.g., crop type, growth stage, planting density, fixture height, light spectrum, electricity rates). Recommend additional agronomic and environmental variables to improve AI-driven simulations. Develop a grower-facing input form to standardize data collection. Propose a mapping framework linking each input to outputs (fixture selection, energy use, yield, ROI). Design a reporting structure for how results can be automated into grower-friendly ROI reports once AI is integrated.
Sustainability-Driven Marketing Strategy for Global Cleantech Directory
The Global Cleantech Directory aims to enhance its reputation as a leader in ecological responsibility by integrating green branding into its consumer and member engagement practices. This project focuses on designing marketing strategies and communication frameworks that emphasize sustainability. The objective is to develop outreach campaigns that highlight the Directory's commitment to ecological responsibility, thereby enhancing brand trust and fostering meaningful engagement with cleantech stakeholders worldwide. By positioning the platform as a leader in promoting responsible consumption and sustainable innovation, the project seeks to strengthen the Directory's role as a trusted platform in the cleantech industry. The project will involve analyzing current engagement practices, identifying opportunities for incorporating green branding, and creating a comprehensive strategy that aligns with the Directory's sustainability goals.
Sustainable Branding Strategy for Global Cleantech Directory
The primary objective of this project is to integrate sustainable branding and consumer engagement practices into the Global Cleantech Directory’s marketing strategy. The project aims to strengthen the platform’s identity as a trusted leader in cleantech by embedding environmental principles, fostering responsible consumption, and enhancing global visibility. Students will analyze consumer trends, explore innovative communication methods, and develop strategies that connect ecological responsibility with brand trust, while aligning with the Directory’s mission to harmonize technology, humanity, and nature.
Designing a Data Schema for AI-Driven Greenhouse and Vertical Farming LED Solutions
Designing a comprehensive data schema and framework for AI-driven LED lighting optimization in greenhouses and vertical farming, with the goal of standardizing agronomic, operational, and environmental inputs into an AI-ready structure. This framework will enable accurate simulations of energy use, crop growth, yield performance, and ROI outcomes, creating a foundation for grower-friendly decision-making tools. By mapping input variables to measurable outputs, the project will guide growers in selecting the most effective lighting solutions that balance productivity, sustainability, and cost-efficiency across diverse controlled-environment agriculture settings.
Designing a Data Schema for AI-Driven Greenhouse and Vertical Farming LED Solutions
The project will produce a structured AI-ready data schema with defined variables, a standardized data collection form for growers, and a mapping framework that links inputs to LED performance metrics. Students will also deliver a comprehensive final report outlining methodology, recommendations, and practical next steps for integrating AI-driven simulations that connect lighting strategies to crop yield, energy efficiency, and ROI in greenhouses and vertical farming.
Custom CRM System for SaaS Sales Optimization
The objective of this project is to build a functional CRM system that supports sales pipeline management. Students will identify and design lead-tracking stages, integrate tools for monitoring conversions, and deliver documentation that ensures usability, scalability, and alignment with our SaaS business model.
UX/UI Design and User Experience Optimization
The objective of this project is to enhance the user interface and overall user experience of our platform. Students will analyze current design challenges, conduct user testing, and deliver wireframes, prototypes, and recommendations to improve accessibility, navigation, and visual consistency.
AI Assistance Prototype Development with Machine Learning
The main objective of this project is to build an AI assistance prototype using machine learning. Students will work on tasks such as dataset preparation, intent recognition, and model training. The goal is to deliver a functional prototype, evaluate performance, and document the development process.
Cleantech Database Design and Implementation
The goal of this project is to design and implement a scalable database that can store, organize, and retrieve public cleantech company data. Students will practice skills in database design, coding (SQL/NoSQL), and query optimization. By the end, the project will deliver a functional database prototype with documentation, preparing the foundation for future integration with AI and CRM systems.
AI-Driven Insights and Lead Prediction for Cleantech Expansion
Company Global Cleantech Directory Connecting cleantech businesses globally to accelerate sustainability and innovation. Project Summary This project will support the Global Cleantech Directory platform by leveraging advanced data analytics and AI to track user engagement, forecast growth, and identify high-value leads. Interns will apply machine learning to real user behavior data and create predictive models and dashboards to help increase conversions and platform adoption. Their work will directly improve decision-making, marketing, and user experience design across the platform. Internship Objectives Build predictive models to understand user intent and likelihood of sign-up or upgrade Analyze user interaction data (listings viewed, chatbot messages, time on page, etc.) Create dashboards that summarize listing engagement, user trends, and regional growth Deliver strategic recommendations to improve business conversion and user retention Integrate data-driven insights with existing chatbot and AI assistant design Tools & Data Languages/Tools: Python, SQL, Tableau, Power BI, Excel Data Sources: Platform activity logs, listing metadata, chatbot transcripts (if anonymized) Collaboration: Slack or Teams, Zoom check-ins, shared Google Drive or Notion for documentation Suggested Skills Intermediate to advanced knowledge of Python (pandas, sklearn, matplotlib) Experience in classification models, clustering, or time series forecasting Familiarity with dashboard tools (Power BI, Tableau) Ability to explain findings to non-technical stakeholders Ideal Student Profile MDA student with strong curiosity and a business mindset Interest in cleantech, sustainability, or digital platforms Able to work independently while meeting key project milestones Timeline Duration: 10–12 weeks (Sept 22–Dec 14, 2025) Estimated hours: 350–480 hours Mode: Remote Why Join This Project? Help a cleantech platform grow faster using the power of AI. Your work will directly influence global business engagement, and you’ll leave with a real-world analytics portfolio that demonstrates high-impact, applied data science.
Global Legal & Tax Framework Research for International Growth of Global Cleantech Directory
Project Overview: As Global Cleantech Directory expands internationally, this project focuses on helping us ensure compliance with two critical areas that impact global digital platforms: data privacy laws and international tax regulations . Students will conduct comparative legal research and practical analysis to ensure we meet the standards of data protection frameworks (like GDPR and PIPEDA) and understand taxation policies across key markets. This focused project enables real-world application of coursework in law, taxation, and international business policy. Project Goals: Research and summarize data protection laws applicable to our platform (GDPR, PIPEDA, etc.) Identify key international taxation policies that affect digital services and cross-border invoicing (e.g., VAT, DST) Provide compliance guidelines for handling international user data and transactions Deliver clear, region-specific summaries that inform internal practices and investor communications Recommend a checklist for legal onboarding of international clients Propose a basic compliance audit framework for future internal review Identify potential risks or penalties for non-compliance in key jurisdictions Analyze how different regulatory requirements may impact user experience or platform features
International Law Assessment for Foreign Expansion
Recently, our organization has begun discussing the possibility of expanding internationally. As we begin to assess the environment and develop a strategy, we want your help in evaluating the laws, and legal processes of properly expanding to new countries. Tasks may include: Identifying the key legal factors for expansion that we may be impacted by including local laws and regulations, taxes, employment, and exporting. Identifying barriers to entering a new country. Determining the best legal structure for our company and outlining the expansion process. Researching options for intellectual property rights and trademark protection of our products/services. Creating a framework for contracts involving the international sale of our goods. Compile a report including all of the above research and writing to be presented to the owner of the company.
CRM Optimization & Lead Generation Strategy Using
Project Overview: The Global Cleantech Directory is a growing B2B platform designed to connect cleantech companies, investors, and decision-makers worldwide. We are seeking a student team to help us strategically implement and optimize CRM for lead generation, CRM management, and email marketing automation to increase platform engagement and drive sales. Project Goals: Set up or audit existing HubSpot CRM for improved user and lead tracking. Design and implement automated email workflows for onboarding, newsletter updates, and re-engagement. Develop lead generation strategies and conversion funnels to attract cleantech businesses. Create a scalable sales pipeline that can track listing owners, trial users, and paid subscribers. Integrate analytics and reporting to monitor CRM and marketing performance.
AI-Powered Engagement & Impact Campaign for LumeSmart Earth Day 2026
About the Project: LumeSmart Earth Day is more than an event — it's a platform for driving climate action, connecting communities, and showcasing cleantech innovation. As we prepare for Earth Day 2026 , we want to launch a creative engagement campaign that uses AI tools to boost visibility, personalize outreach, and measure real impact . This project invites learners to design and simulate an end-to-end digital campaign powered by AI — targeting students, businesses, local communities, and environmental leaders across Canada and globally. Project Objective: Design an AI-enhanced engagement and awareness campaign for Earth Day 2026 that: Builds momentum before the event Increases attendee interaction during the event Measures and reports climate or social impact afterward
Revenue & Sponsorship Strategy for LumeSmart Earth Day 2026
About the Project: LumeSmart Earth Day is an established, independently-led sustainability conference and trade show, celebrating over a decade of impact in Canada’s cleantech and environmental sectors. As we look ahead to Earth Day 2026 , our goal is to design a creative, community-centered, and revenue-sustainable event that attracts cleantech leaders, youth, educators, startups, and civic partners. This project invites learners to build a comprehensive strategy and sales plan for LumeSmart Earth Day 2026, with a strong focus on: Revenue generation Creative sponsorship models Modern event elements that can elevate visibility, participation, and financial stability Project Objective: Develop a revenue and sales strategy for LumeSmart Earth Day 2026 by: Analyzing our past approach and market trends Proposing creative revenue streams (e.g., AI booths, virtual access passes, eco-product pop-ups) Updating our sponsorship/exhibitor packages Building a target list and outreach plan
AI-Integrated Business Strategy for Expanding LumeSmart Earth Day
About the Project: LumeSmart Earth Day is a decade-strong sustainability conference and trade show that connects clean technology leaders, civic partners, and youth to drive environmental action. As we plan for our next phase of growth, we want to explore how AI tools can enhance our business strategy — from outreach and sales to content and operations. This project invites learners to apply their knowledge of AI tools in business , and help us create a targeted strategic growth plan supported by real AI use cases. Rather than build tools from scratch, students will use existing AI technologies to identify, simulate, or test business enhancements for the conference. Project Objective: Develop a focused business growth strategy for LumeSmart Earth Day with 1–2 AI-powered applications that strengthen event operations, marketing, or sponsorship development.
AI-Powered Lighting Advisor for Greenhouses and Vertical Farming
About the Project: LumeSmart Inc. is a woman-owned Canadian cleantech company founded in 2013. We specialize in LED lighting solutions for agricultural, commercial, and residential use. Our goal is to support sustainable local food production by helping growers — from greenhouses to vertical farms — access the right lighting systems for their crops. This project invites students to build a basic AI-powered tool that simulates how a grower might input simple information (e.g., crop type, square footage, growing environment), and receive a lighting recommendation output based on internal data we provide. This prototype will support LumeSmart’s sales and consulting process and will help us better engage customers interested in sustainable farming. Confidential Use Statement: This tool is intended for internal business use only at LumeSmart. It will be used to support customer recommendations, and the information it provides will be free only to clients who purchase our LED products . Students will work under a non-disclosure agreement (NDA) to protect proprietary data, and will be encouraged to focus on the technical logic and tool-building , not on business operations or product decisions. Objectives (Refocused and Clear): Build a prototype system or chatbot that accepts grower inputs (e.g., crop type, growing method, area size). Map these inputs to a structured logic or database (provided by LumeSmart) to generate simple lighting suggestions. Output results such as: “Recommended: LumeSmart X100, Qty: 12, Spectrum: Full Red/Blue” in a basic web form or chatbot. Ensure the tool structure can be scaled in the future with more crops or product types.
Sales Development for LED Lighting – Supporting Energy Efficiency in Canadian Buildings
About the Project: LumeSmart Inc. is a woman-owned Canadian cleantech company, operating since 2013. We specialize in high-efficiency LED lighting solutions for commercial, residential, and institutional clients across Ontario and beyond. Our mission is to reduce energy costs and carbon footprints through smart lighting upgrades — backed by programs like Save on Energy , where we help clients apply for incentives that reduce upfront costs. This project is ideal for business students interested in real-world sales , outreach, and customer engagement. You will support our goal of identifying new sales leads and connecting with decision-makers in offices, retail, warehouses, condos, and residential sectors. Project Objectives: Identify potential clients (businesses, property managers, or homeowners) who would benefit from LED upgrades. Create an organized lead list with contact details and basic qualification notes. Support initial outreach via phone, email, or LinkedIn (with templates provided). Participate in or help schedule introductory calls with interested leads. Reflect on the sales process and provide ideas for improving outreach efficiency.
MERN Stack Website Rebuild for Global Cleantech Directory
The Global Cleantech Directory is seeking to enhance its online presence by transitioning its existing WordPress website to a more robust and modern MERN (MongoDB, Express.js, React, Node.js) stack. This project aims to improve the website's performance, scalability, and user experience, addressing current limitations in customization and security. By leveraging the MERN stack, the new website will offer modern web functionalities that align with industry standards. This project provides learners with the opportunity to apply their classroom knowledge in full-stack web development, focusing on both front-end and back-end technologies. The team will work collaboratively to ensure a seamless transition, maintaining the integrity of existing content while enhancing the overall user interface and experience. The project is designed to be completed within 80 hours, allowing learners to gain practical experience in a real-world setting.