ThermaFY develops software that can analyse heat patterns by pairing thermal cameras with machine learning. Thermal data insights can help us identify and understand temperature conditions – whether the challenge is patients with a fever, or livestock health, or energy waste in buildings.Learn about ThermaFY
From global health crises to climate change – many of the challenges we face today can be identified as heat anomalies. Thermal radiation can only be seen using thermal imaging cameras, which can be expensive and difficult to interpret without expertise, creating a high bar to entry for this critical tool. Early identification of temperature anomalies can result in more timely and responsive actions. For example, farmers can use thermal data to diagnose infection and disease in livestock more quickly and at scale. Energy companies can use thermal data to identify faulty heating systems to reduce waste and emissions.
ThermaFY makes thermal analysis more accessible. Combining the latest advancements in thermal cameras with innovative software, ThermaFY provides user-friendly applications that track heat patterns and trends over time. Microsoft Azure machine learning models process the images and calculate useful metrics. Reporting technology then visualises the data in easy-to-use web dashboards. People can use this data to unlock insights and solve problems faster, whether it’s quickly detecting fever in patients, identifying sites of infection in livestock or reducing energy inefficiencies in buildings.
Solving inefficiencies with thermal data
Capturing thermal data with a thermal camera has proven to be extremely beneficial across all industries. It can identify inefficient energy loss, locate electrical faults and help diagnose medical conditions. ThermaFY provides data insights to make more informed decisions across many industries aligning to the company’s key values of sustainability and social good.
How ThermaFY works
ThermaFY’s imaging camera captures images and temperature data from the otherwise invisible light spectrum. Their software on Microsoft Azure uses machine learning to calculate useful metrics through image and data processing. Visual reports display results in an understandable format for end users.
How ThermaFY uses Azure
- SQL Database for scaling databases without worrying about capacity.
- Data Lake Storage for storing high volumes of data and images.
- Virtual Machines for providing the processing power to provide quick on-demand results.
- Cognitive Services for identifying features within optical and thermal images to help build recognition models that capture temperature data of specific areas.
- Face for creating a more secure system for hospitals by identifying key people when entering the building.