AWS for Industries
Category: Amazon SageMaker
The Cow Collar Wearable: How Halter benefits from FreeRTOS
Who is Halter, and what IoT product are they building? Halter (https://halterhq.com), based in New Zealand, is an agri-tech original equipment manufacturer (OEM) that focuses on cattle herd management. Halter creates GPS enabled, solar powered smart collars for cows. The collar hardware allows farmers to interact with an easy-to-use app to remotely set geographic boundaries […]
Planning for recovery: 5 trends to watch in travel and hospitality’s new normal
Previously, we have discussed how organizations have been stabilizing operations by aggressively optimizing costs, leveraging technology to support remote working, contact centers and ensuring both workforces and customers are safe. This is a complex and involved situation: ensuring maintaining a viable business, whilst balancing people and services, especially without a clear view of how and […]
How utility executives elevate the customer experience with Amazon Connect
Utility executives share common benchmark success metrics when reporting to stakeholders including customers, regulators, elected officials, and investors. Regulated investor-owned utilities focus on long-term metrics such regulated rates of return (ROR) and service reliability benchmarks such as Customer Average Interruption Duration Index (CAIDI). Energy retail executives focus closely on customer satisfaction (CSAT) scores and customer […]
How OAG Analytics leverages AI and machine learning to optimize the profitability of oil and gas wells
In 2013, Luther Birdzell formed OAG Analytics to create an AI platform that enables oil and gas companies to use more of their data to help solve critical problems like well spacing. Today, the OAG-Amazon SageMaker integration enables customers to unify their datasets and create proprietary analyses using virtually unlimited compute. READ MORE Click here […]
Kinect Energy uses Amazon SageMaker to forecast energy prices with machine learning
The Amazon ML Solutions Lab worked with Kinect Energy recently to build a pipeline to predict future energy prices based on machine learning (ML). We created an automated data ingestion and inference pipeline using Amazon SageMaker and AWS Step Functions to automate and schedule energy price prediction. READ MORE Click here to learn more about Energy on AWS
Digging deep and solving problems: Well Data Labs applies machine learning to oil and gas challenges
When CEO Josh Churlik co-founded Well Data Labs in 2014, he was acutely aware of a bizarre dichotomy in his industry: For oil and gas companies, “downhole” innovation (that is, what happens underground) far exceeds the pace of data and analysis innovation. The data systems used then were relics of the 1990s – more homages to history […]
AWS IoT analytics oil and gas customer use case
Learn how an oil and gas company deployed AWS IoT Analytics to help them better understand their assets in the field, derive actionable insights from their data, and build a predictive maintenance solution to help reduce their costs. READ MORE Click here to learn more about Energy on AWS
Interpreting 3D seismic data automatically using Amazon SageMaker
Interpreting 3D seismic data correctly helps identify geological features that may hold or trap oil and gas deposits. Amazon SageMaker and Apache MXNet on AWS can automate horizon picking using deep learning techniques. In this post, I use these services to build and train a custom deep-learning model for the interpretation of geological features on 3D seismic data. The […]
Harvest needs: Farms need labor and innovation
Food is the thread that connects us all, and in times of stress or uncertainty, the reliance on our food producers has never been so clear. From the fields of strawberries, cherries and citrus to the rice, lentils and bread on your plate, all are the product of the generations of farmers who have invested […]
Forecasting energy usage using Amazon machine learning and data lakes
Executives within utilities and energy providers of all types and sizes have multiple ongoing needs to forecast energy usage. For example, as chief customer officer, your teams can use energy forecasts at the household level to proactively engage homeowners with high bill alerts and predict pre-pay or month-end energy charges. As the head of energy […]