Aurai is a cloud-based platform that makes is easy to apply Artificial Intelligence (AI) to indoor climate and health sensor data. With a pre-built library of data signatures that automatically detect a number of indoor climate and comfort situations, Aurai makes it easy to add artificial intelligence to indoor climate and health controls. For instance, Aurai includes data signatures for detecting solar loading, duct leakage issues, and mold risk. Aurai is essentially AI-as-a-service for indoor climate and health companies.
Easy to Set Up
The Aurai platform requires minimal setup— devices can send sensor data the moment they come online, no registration required.
Capable of processing hundreds-of-thousands of data points per second, and support for a variety of protocols like HTTP and MQTT, Aurai is ready for anything you throw at it.
A Data Lake of Exabyte Proportions
Data science evolves over time, and historical data is key to training machine learning models and optimizing algorithms. You should never have to choose between data that matters now and data that might matter in the future.
The Aurai platform allows you to easily, cost-effectively, and efficiently store exabytes worth of historical sensor data, and to extract that data in seconds using a simple point-and-click UI or SQL statements.
Indoor Data Science Made Easy
Data science is hard, and building a data science team is even harder. Incorporating data science and machine learning into your indoor IoT product or service should be easy.
The Aurai platform automates the logistics of mapping, packaging, delivering, and responding to the analysis of your data.
Predicting mold and condensation damage, diagnosing equipment problems, efficiency monitoring and tuning, detecting air quality problems, and much more is as simple as choosing a data signature.
Alerts and Reporting
Data analysis is meaningless until it gets to the right person (or thing) in a timely fashion.
The Aurai platform automates the scheduling and delivery of data analysis to a multitude of destinations, including mobile app push notifications, emails, spreadsheets, webhooks, and PDF reports.
ConnectM has several pre-built data signatures that you can start using immediately. Our global pool of data scientists are continually developing and curating a wide range of artificial intelligence capabilities. Current data signatures includes capabilities for:
Mold Risk. This data signature detects when an indoor space meets the conditions where mold may reproduce. This signature requires the presence of temperature and humidity sensors. It can trigger an alert to a homeowner and/or service technician.
Air Quality. This data signature detects when certain air quality conditions are met. This signature works with a wide variety of sensors, such as particulate matter, volatile organic compound, and carbon dioxide sensors. It can trigger the running of HVAC fan, or other ventilation system, to disperse locally high concentration of harmful matter.
Freezing Coils. This data signature detects when the coils of an air conditioning unit freeze. This data signature requires the presence of temperature and pressure sensors. It can trigger an alert to a homeowner and/or service technician.
Equipment Short Cycling. This data signature detects when undesirable short cycling of an HVAC unit is occurring. This data signature requires the presence of a thermostat. It can trigger an alert to a homeowner and/or service technician.
Replace Filter. This data signature detects when the filter in an HVAC system needs to be replaced. This data signature required the presence of pressure sensors. It can trigger an alert to a homeowner and/or service technician.
Heat Exchanger Risk. This data signature detects when a heat exchanger experiences the conditions that lead to a crack in the housing. This data signature requires the presence of a temperature sensor. It can be used to proactively shut down in the HVAC unit before a potentially critical event occurs, and could trigger an alert to both the homeowner and service technician.
Unusual conditions. This capability "learns" the typical conditions for your indoor space, and can trigger an alert when unusual conditions exist.
ConnectM also makes it easy for you to create your own data signatures and machine learning capabilities.
For Aurai API documentation, see developer.aurai.io/docs/