Literature Review on Mycelium Fire-Retardant

Bayes Studio is exploring innovative solutions to prevent wildfires using natural materials. This project focuses on compiling, analyzing, and synthesizing existing research on mycelium as a fire-retardant. The primary goal is to understand the current landscape of mycelium-based fire-retardant research, identify any knowledge gaps, and provide insights that can guide future research and innovation efforts at Bayes Studio. By leveraging existing studies, the project aims to assess the effectiveness of mycelium in fire prevention and its potential applications. This will help Bayes Studio in strategizing their research direction and innovation in sustainable fire-retardant solutions.

Identifying Pain Points in Wildfire Detection and Management: Insights from Governmental Firefighting Agencies

The goal of this project is to gain actionable insights into the operational, technological, and resource-related pain points faced by governmental firefighting agencies in wildfire detection and management. By engaging directly with key stakeholders through interviews, the project aims to uncover critical challenges and gaps, enabling Bayes Studio to develop and tailor innovative AI-driven solutions that enhance wildfire monitoring, response efficiency, and community safety.

Wildfire Data Analysis and Prediction

The Wildfire Data Analysis and Prediction project aims to provide learners with hands-on experience in data analytics and predictive modeling using real-world environmental data. The project involves exploring and analyzing two comprehensive wildfire datasets: NASA’s FIRMS and SatFire. Learners will focus on understanding regional distribution and identifying trends in wildfire occurrences. The primary goal is to create an interactive visualization that effectively communicates these insights. Additionally, learners will develop a statistical or machine learning model to predict future wildfire occurrences. This project will enhance learners' skills in data visualization, statistical analysis, and predictive modeling, contributing to improved wildfire management strategies.

Literature Screening for Carbon Measurement Integration

Students will engage in the following tasks and activities to achieve the project goal: 1. Literature Review and Screening Task: Perform a comprehensive review of academic literature, white papers, and industry reports on carbon measurement technologies. Activity: Identify key technologies such as infrared gas analyzers, LIDAR, hyperspectral sensors, and others. Deliverable: A detailed literature review report highlighting the most relevant carbon measurement methods. 2. Technology Comparison and Feasibility Analysis Task: Compare the identified carbon measurement technologies based on factors like accuracy, range, power efficiency, weight, and compatibility with the our aerial vehicle. Activity: Conduct a comparative analysis, considering how each technology could be adapted to our UAVs. Deliverable: A feasibility matrix comparing the technologies and a recommendation report on the most suitable options. 3. Application Area Analysis Task: Research and analyze areas of interest where carbon measurement is most impactful, such as wildfire emissions, forest carbon sequestration, and urban-industrial monitoring. Activity: Identify key global regions and sectors where Bayes Studio’s aerial vehicle could provide carbon measurement data, complementing its wildfire monitoring. Deliverable: A report outlining the areas of interest with data on carbon impact and potential monitoring opportunities. 4. Sensor Integration Requirements Task: Outline the technical specifications required for integrating carbon measurement sensors into the aerial system. Activity: Work with technical specifications for sensor weight, power consumption, data transmission, and sensor accuracy. Deliverable: A technical requirements document that outlines the key factors to consider for sensor integration.

Indigenous Wildfire Resilience

Bayes Studio aims to enhance its wildfire monitoring and management solutions by making them more culturally sensitive and effective for Indigenous communities. The project involves conducting interviews with members of Indigenous communities to identify their specific needs and preferences regarding wildfire monitoring and management. This will help Bayes Studio tailor its solutions to better align with the cultural values and practical requirements of these communities. The ultimate goal is to foster collaboration and resilience, ensuring that the solutions provided are both respectful and effective. The project will provide learners with the opportunity to apply their knowledge of community engagement, data collection, and cultural sensitivity in a real-world context. Key tasks include: - Designing interview questions that are culturally appropriate and relevant. - Conducting interviews with members of Indigenous communities. - Analyzing the collected data to identify common themes and specific needs. - Compiling a comprehensive report with recommendations for Bayes Studio.

Customer Connections

Project Description : Customer Connections Our project, "Customer Connections," aims to deeply understand the needs, challenges, and preferences of our target market through comprehensive customer interviews. This initiative will enable Bayes Studio to refine our product offerings and tailor our marketing strategies effectively, enhancing product development and customer satisfaction. The interns will engage in roles such as conducting customer interviews, developing and administering surveys, and analyzing data to inform product and marketing strategies. Main Goal : Deep Market Understanding: To gain a comprehensive understanding of the needs, challenges, and preferences of the target market through detailed customer interviews and surveys. Product and Marketing Refinement: To refine and tailor Bayes Studio’s product offerings and marketing strategies based on the insights gathered from customer feedback, thereby directly contributing to improved product development and increased customer satisfaction. Data-Driven Decision Making: To collect, organize, and analyze qualitative and quantitative data from customer interactions, which will inform and guide strategic product development and marketing initiatives. Development of Customer Personas: To create detailed customer personas based on collected data, helping the marketing and product teams better understand and target potential customers effectively. Strategic Recommendations: To provide actionable insights and recommendations for future customer engagement strategies and continuous improvement of the customer interaction process.

Vision Nest: Wildfire Monitoring & Management Hub - Backend and Admin panel

Background : Vision Nest is an innovative AI-powered IoT system designed for the early detection of wildfires in remote locations. Our system comprises stationary units equipped with an array of sensors including cameras, thermal imagery, and air quality sensors. These units periodically transmit data to our central servers via POST requests, ensuring real-time monitoring capabilities. Challenge : Despite our robust data collection capabilities, we currently lack an efficient way to show and interact with the data from these devices. Our goal is to improve the current comprehensive admin panel that enables effective management and monitoring of the Vision Nest units, facilitating rapid response and detailed environmental analysis. Tech stack: GCP (mainly cloud run, pub/sub, and cloud functions, VertexAI end-points), React, TypeScript, Bootstrap Objective : By the end of this project, learners are expected to create an admin panel with the following functionalities: User Authentication: Secure login for users to access their specific Vision Nest devices. Device Management Settings : Module for users to configure and update device settings remotely. Geographical Visualization : Interactive map displaying the locations of all deployed Vision Nest units, with clickable options for detailed data views. Data Visualization : Periodically updating charts displaying air quality metrics and the latest visual data from each device linked to the user's account. Snap shot : Snap shot of the devices latest reading. Outcome : Participants will deliver a user-friendly admin panel that not only enhances the usability of the Vision Nest system but also supports crucial wildfire prevention efforts by providing timely and actionable insights.