Your IoT platforms, systems, and devices have opened new possibilities for businesses. Now by adding the power of AI to your IoT system, you can lead the next wave of disruptive innovation!
The convergence of technologies like AI, Machine Learning and NLP, etc., with IoT, can open new opportunities. So, if you own an IoT product or platform, you can add several new capabilities to it derived from these methodologies. The AI Management System-IoT integration will be more powerful than two technologies working in silos. As Aristotle said: “The whole is greater than the sum of its parts.”
How Can AI & IoT work together?
IoT devices collect a vast amount of data through sensors, chipsets, cameras, and apps, etc. Inherent in this data is information that can power insights, detect anomalies, identify performance attributes, predict events and simulate what-if scenarios for your IoT system. Extracting this hidden intelligence from the information gathered is crucial in truly transforming your IoT platform capabilities, accelerating its performance, and helping deliver innovative solutions to your customers.
A few examples of the Intelligence that can be derived from IoT data are –
- Asset Tracking
- Predictive Maintenance
- Incident Tracking
- Demand Prediction
- Capacity Planning
- Regional & Seasonal Demand Prediction
- Supply & Distribution
- Real-time Usage
- Historic Usage
- Usage Predictions
- Average Usage Metrics
- Safety Tracking & Usage Deviations
How Can Qualetics Help you power your IoT product with AI?
Qualetics is our on-demand AI management system (AIMS) that can help IoT product or platform owners derive hidden information and intelligence in the data they are collecting and also serve crucial insights and metrics in a real-time and cost-efficient manner. Our proprietary platform allows for easy Data Management, Data Analysis, and Data Visualizations to power your Products & Systems.
A recent use case where IoT and Qualetics Data Intelligence came together was when we created a model for real-time ingestion of LPG Cylinder consumption data using weight sensors. Coupled with other information, we were able to not only present current usage, incidents, and bookings, we were also able to show predicted usage by consumers, forecasted bookings for dealers, and seasonal trends impacting LPG usage in residential customers.
To implement a similar seamless solution to analyze the data captured by your IoT platform, the following are key components that Qualetics offers which can be leveraged by an IoT platform –
Secure and stable Data Management
Qualetics has developed its proprietary data ingestion API that can transmit extremely high volumes of data typical of an IoT network. Our clients are provided with secure credentials and some specific configuration that allows data from the device network to be transmitted to the servers.
Data Virtualization to store, clean, and transform vast amounts of data
Data ingested through our API is stored in high volume storage after going through several stages of transformation that involve data validation and deduplication. This will provide an in-depth understanding of the intrinsic value of the captured data and transforming it into information.
Data Analysis to identify features, build and train models
With the data securely stored in the storage layer, models that are designed and developed, specific to the incoming data structures are applied automatically to analyze the data in real-time and render the results to our output layer. Certain use cases require continuous analysis of historic data as well, which is conducted in the same system.
Data Delivery & Visualization platform
Results generated through the analysis layer are available through our dedicated customer portal which contains several features for viewing results such as filtering, sharing, subscribing to changes in data, and also exporting the analyzed results into different formats, thus providing an opportunity to see hidden patterns.
In addition to a visualization platform, the portal also provides an API for developers who wish to integrate the visualizations or raw results natively into their applications. Doing so allows the developer to control the entire user experience of its users to the application features and advanced analytical results natively within a single client application.