Fuels Data: App Testing With Wildland Practitioners | by Wildlands | Jul, 2023

Testing Apps in the Wild: Empowering Wildland Practitioners with Fuels Data | by Wildlands | July 2023

Introduction:

In the face of increasing wildfires and their devastating impact on the environment and human health, AI2’s Wildlands team has developed an innovative solution to aid field practitioners in their efforts to combat these destructive fires. The Fuels Data app is a powerful tool that streamlines the process of collecting data in the field, provides tools to summarize the collected data, and constructs a dataset for future AI models. During a recent training workshop at Turnbull National Wildlife Refuge, the app was put to the test by a group of field practitioners, who were impressed by its efficiency and accuracy. With ongoing development and feedback from practitioners, the Fuels Data app aims to revolutionize the way wildfires are managed and controlled. If you are interested in partnering with the Wildlands team and trying out the app, contact them at wildland-fire-team@allenai.org.

Full Article: Testing Apps in the Wild: Empowering Wildland Practitioners with Fuels Data | by Wildlands | July 2023

Wildfires Continue to Plague North America Despite Changing Seasons

As we enter the summer season in North America, wildfires have become a prevailing issue, causing concerns about air quality and long-term impacts. Formerly limited to the summer months, fire season now extends year-round due to climate change. The intensification of fires is a global concern, affecting not only the West Coast of the United States but also regions worldwide. These wildfires pose significant risks to our health and well-being.

Historic Wildland Management Practices and the Need for Change

Traditional wildland management practices focused on quickly suppressing any fire, preventing the natural benefits of fire in fire-adapted ecosystems. Consequently, excessive fuel accumulation and disruptions in vegetation cycles have made wildlands more vulnerable to extreme fires. To mitigate the risk, it is crucial to restore wildlands to a natural fire-adapted state and prioritize fuels reduction efforts. Techniques such as mechanical thinning and controlled burns help reduce fuels. However, planning such activities requires accurate measurement of surface fuels before and after the reduction treatment.

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Introducing the Fuels Data App

In response to the need for efficient data collection and analysis, the AI2 Wildlands team has developed an app called Fuels Data. This app aims to simplify the work of field practitioners by providing tools to collect and summarize data while constructing a dataset suitable for training AI models. The app was tested in the field during a training workshop at Turnbull National Wildlife Refuge, involving a group of practitioners led by Heather Heward, a senior Fire Ecology & Management instructor at the University of Idaho.

Benefits of the Fuels Data App

During the workshop, participants were trained in both the traditional photoloading process using pen and paper and the app-enabled process. The app proved to be a valuable tool, performing calculations on the spot and eliminating the need for manual calculations. Additionally, attendees appreciated the convenience of having all their data organized within the app. The app’s user-friendly interface and ability to save time and enhance accuracy were highly praised by workshop participants.

The Future of Fuels Data

The Wildlands team has been actively gathering feedback from practitioners to refine the Fuels Data app. Incorporating user suggestions and requests into their roadmap, the team aims to further improve the app’s functionality. They are developing models to support semi-automatic estimation of fuel components in captured images, starting with estimates of down dead and woody fuels. The team also plans to expand the app’s capabilities to detect additional classes of fuel.

Get Involved

The Wildlands team is actively seeking practitioners who wish to partner with them and test the Fuels Data app. For inquiries and partnerships, please contact the team at wildland-fire-team@allenai.org. The app is currently available for download in its early version on the app stores for iPhone, iPad, and Android.

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Training Workshop at Turnbull National Wildlife Refuge

The training workshop conducted at Turnbull National Wildlife Refuge provided valuable insights into the challenges faced by field practitioners in rugged terrain conditions. The Wildlands team’s participation in the workshop allowed them to experience firsthand the difficulties encountered by practitioners, informing their plans for making usability improvements to the app, including a feature to organize field photos.

Overall, the Fuels Data app shows promise in revolutionizing the way field practitioners collect and analyze data related to wildfires and fuel reduction efforts. With ongoing development and collaboration with practitioners, the app has the potential to significantly enhance wildfire management strategies and contribute to the preservation of our wildlands.

Summary: Testing Apps in the Wild: Empowering Wildland Practitioners with Fuels Data | by Wildlands | July 2023

As wildfires continue to be a widespread issue in the United States, the need for effective wildland management practices becomes crucial. Paul Albee, Principal Research Engineer on AI2’s Wildlands team, has developed the Fuels Data app to assist field practitioners in measuring surface fuels before and after fuels reduction treatment. The app simplifies data collection, provides tools for data summarization, and constructs a dataset for training AI models. The app was recently tested at Turnbull National Wildlife Refuge during a photoloading workshop and received positive feedback from practitioners. The team is actively seeking partnerships with practitioners to further improve the app and make their work easier.

Frequently Asked Questions:

Q1: What is Artificial Intelligence (AI)?

AI, short for Artificial Intelligence, refers to the simulation of human intelligence in machines designed to mimic human-like behaviors and cognitive functions. It involves the creation and programming of smart computer systems that can learn, reason, and make decisions autonomously, without explicit human intervention.

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Q2: How does Artificial Intelligence work?

At its core, AI relies on data processing and algorithms to enable machines to learn from experience and patterns. Machine learning, a subset of AI, helps computers analyze vast amounts of data, recognize patterns, and make predictions or decisions based on learnings. Deep learning, another subset, further enhances AI capabilities through the use of neural networks that mimic the human brain’s structure.

Q3: What are the practical applications of Artificial Intelligence?

AI has numerous applications across various industries and domains. Some common examples include:

1. Healthcare: AI helps in medical diagnosis, drug discovery, robotic surgeries, personalized treatment plans, and patient monitoring.
2. Finance: AI aids in fraud detection, algorithmic trading, risk assessment, and personalized financial recommendations.
3. Automotive: AI powers self-driving cars, advanced driver-assistance systems (ADAS), and intelligent traffic management.
4. Customer Service: AI chatbots and virtual assistants assist in resolving customer queries and providing personalized support.
5. E-commerce: AI enables personalized product recommendations, demand forecasting, and efficient supply chain management.

Q4: What are the potential benefits and challenges of AI?

The benefits of AI include increased efficiency, improved decision-making, enhanced productivity, and various breakthrough advancements in different fields. However, challenges associated with AI include:

1. Ethical Concerns: AI raises questions regarding privacy, bias, and the potential impact on jobs.
2. Data Privacy and Security: AI systems require access to large amounts of data, which may pose privacy risks if mishandled.
3. Technical Limitations: AI algorithms heavily rely on quality and quantity of data, and limitations in data availability or quality can affect performance.
4. Skilled Workforce: The need for individuals with expertise in AI is rapidly increasing, leading to a potential skills gap in workplaces.

Q5: What is the future of Artificial Intelligence?

The future of AI is promising and holds significant potential in shaping various aspects of our lives. Advancements in AI technologies may lead to breakthroughs in healthcare, transportation, education, and other critical domains. However, the ethical and societal implications must be carefully considered to ensure responsible and equitable adoption of AI. Continued research, collaboration, and regulation are essential to harness AI’s full potential while mitigating any potential risks.