Due to erratic climate change, human activities, and land-use patterns, wildfires have emerged as a mounting threat to ecosystems. Apart from immediate devastation to biodiversity and natural habitats, they cause repercussions such as adverse effects on properties, health, and air quality. A proactive approach to predicting the dynamics of wildfires can help minimize the loss through timely assistance.
An Intel® Student Ambassador, Joel John Joseph, developed an Intel® oneAPI-based project that aims at wildfire behavior prediction, especially the time it takes to extinguish a wildfire. It also shows a visual representation of the geographical data indicating the wildfire distribution. The Python* solution combines data analysis, machine learning, and geospatial visualization.
Check out the complete project on GitHub.
About the Intel® Student Ambassador
Joel John Joseph is currently pursuing a Masters in Computer Applications at Christ (deemed to be university) in Bangalore, India. As an Intel Student Ambassador, he has had an opportunity to exhibit the innovative use of oneAPI to fellow students by hosting various seminars, workshops, and hackathons.
Intel’s Tools and Technologies Used in the Project
The wildfire dynamics prediction project leverages the following software components on the Intel® Developer Cloud platform:
- Intel® Integrated Performance Primitives (Intel® IPP)
- Intel® oneAPI Data Analytics Library (oneDAL)
- Intel® oneAPI Deep Neural Network Library (oneDNN)
- Intel® Extension for TensorFlow*
The oneAPI libraries and framework optimizations used in the project enable accelerated and optimized data pre-processing and deep learning model development. They allow the project to seamlessly execute on Intel® CPUs, overcoming architecture-specific challenges.
Learn About Intel® Integrated Performance Primitives (Intel® IPP)
Intel IPP is a multi-threaded library that provides production-ready, domain-specific functions optimized for Intel’s architectures. It helps you build high-performance cross-platform applications related to cryptography, image and signal processing, data compression, and more.
Read the Intel IPP documentation.
Check out the Intel IPP Cryptography GitHub repository.
Intel® oneAPI Data Analytics Library (oneDAL): An Overview
oneDAL enables accelerated development of efficient data science applications on CPUs and GPUs. Optimized implementations of popular machine learning algorithms help you perform faster data preprocessing, data analysis, and model predictions.
For detailed information, refer to the oneDAL documentation.
Check out the oneDAL code samples on GitHub.
Explore Intel® oneAPI Deep Neural Networks (oneDNN) Library
oneDNN enables accelerated and optimized deep learning on CPUs and GPUs. It improves the performance of deep learning frameworks such as PyTorch*, TensorFlow*, OpenVINO™ toolkit, and AI Tools from Intel.
Find more details in the oneDNN documentation.
Check out the oneDNN code samples on GitHub.
Learn About Intel® Extension for TensorFlow*
Intel Extension for TensorFlow is a plugin that up-streams several optimizations into the open-source TensorFlow framework for accelerated deep learning on Intel’s CPUs and GPUs. It enables plugging an XPU into TensorFlow, leveraging Intel’s hardware capabilities to supercharge the AI application.
For details, read our blog and see the Intel Extension for TensorFlow documentation.
Check out the Intel Extension for TensorFlow code samples on GitHub.
What’s Next?
Dive deeper into the ‘wildfire prediction with oneAPI’ project. Also, get started with Intel IPP, oneDAL, oneDNN, and Intel Extension for TensorFlow – unleash the power of these oneAPI components for accelerated AI/ML and data science applications.
We encourage you to explore other AI, HPC, and Rendering tools in the oneAPI-powered software portfolio.
Get the Software
Intel IPP, oneDAL, and oneDNN are available as parts of the Intel® oneAPI Base Toolkit (Base Kit). Intel Extension for TensorFlow is available in the AI Tools Selector.
You can also download stand-alone versions of Intel IPP, oneDAL, oneDNN, and Intel Extension for TensorFlow.
Experiment with oneAPI components on Intel’s latest hardware on the Intel Developer Cloud.
Useful Resources
Technical Software Product Marketing Engineer, Intel
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