{"slug":"minesense-uses-machine-learning-on-sensor-data-to-distinguish-high-grade-ore-from-waste-in-real-time","url":"https://findausecase.com/use-cases/minesense-uses-machine-learning-on-sensor-data-to-distinguish-high-grade-ore-from-waste-in-real-time","title":"MineSense uses machine learning on sensor data to distinguish high-grade ore from waste in real time","description":"MineSense combines rugged X-ray fluorescence sensors on mining equipment with advanced machine learning models to estimate ore grade in every shovel bucket in real time, helping mines make smarter routing decisions, improve metal recovery, and reduce waste. Running on Oracle Autonomous AI Lakehouse, MineSense also uses OCI generative AI agents with retrieval-augmented generation to automate knowledge-base searches, improving field engineering productivity 5X and reducing DBA workloads by 65%.","company":"MineSense Technologies","industry":"Energy","country":"Canada","aiCapabilities":["Machine Learning","Retrieval-Augmented Generation","Large Language Models"],"technology":["Oracle Cloud Infrastructure","Oracle Autonomous AI Lakehouse","Oracle APEX","OCI Generative AI Agents","OCI Functions","OCI Interconnect for Azure","Oracle Data Studio","OCI Object Storage","Oracle Select AI"],"deployment":"Public Cloud","problemStatement":"To support its data-intensive workflow at scale, MineSense needed a powerful, flexible cloud data platform that could integrate large volumes of diverse industrial IoT data from mining operations, support analytics and machine learning, and help teams deliver secure, near real-time insights to customers.","solutionApproach":"MineSense chose Oracle Cloud Infrastructure with Oracle Autonomous AI Lakehouse to support its modern lakehouse architecture and automate data integration; its rugged X-ray fluorescence sensors installed on mining equipment scan material at the extraction face and, combined with advanced machine learning models, estimate ore grade in every shovel bucket in real time. OCI generative AI agents combine large language models with retrieval-augmented generation to automate searches across the company's knowledge base, and Oracle Select AI lets staff simplify sensor support requests and assist with database monitoring and performance tuning.","businessValue":"MineSense's small IT team lowered DBA workloads by 65% while supporting rapid growth in customers and data volumes; OCI generative AI agents improved field engineering productivity by 5X and saved hundreds of hours per year in development and maintenance time, and Oracle APEX let staff build and deliver low-code apps in one week instead of six.","evidence":{"band":"high"},"sourceUrl":"https://www.oracle.com/customers/minesense-autonomous-database/","dates":{"publishedAt":"2026-09-09T09:01:30.685Z","publishedAtSource":"pipeline","updatedAt":"2026-09-09T09:01:30.685Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/minesense-uses-machine-learning-on-sensor-data-to-distinguish-high-grade-ore-from-waste-in-real-time. Bulk republication requires permission."}