AI is the engine that will enable analytics and decision making from the data collected by IoT. For companies to realize the full potential of IoT enablement, they need to combine IoT with rapidly-advancing Artificial Intelligence, which enable machines to simulate intelligent behavior and make well-informed decisions with little or no human intervention.
In an IoT situation, AI can help companies take the billions of data points they have and boil them down to what’s really meaningful. The general premise is the same as in the retail applications – review and analyze the data you’ve collected to find patterns or similarities that can be learned from, so that better decisions can be made.
To be able to call out potential problems, the data has to be analyzed in terms of what’s normal and what’s not. Similarities, correlations and abnormalities need to be quickly identified based on the real-time streams of data. The data collected, combined with AI, makes life easier with intelligent automation, predictive analytics and proactive intervention.
AI and IoT Data Analytics
There are several types of IoT Data Analysis where AI can help:
- Data Preparation: Defining pools of data and clean them which will take us to concepts like Dark Data, Data Lakes.
- Data Discovery: Finding useful data in the defined pools of data
- Visualization of Streaming Data: On the fly dealing with streaming data by defining, discovering data, and visualizing it in smart ways to make it easy for the decision-making process to take place without delay.
- Time Series Accuracy of Data: Keeping the level of confidence in data collected high with high accuracy and integrity of data
- Predictive and Advance Analytics: a Very important step where decisions can be made based on data collected, discovered and analyzed.
AI in IoT Applications:
- Visual big data, for example, will allow computers to gain a deeper understanding of images on the screen, with new AI applications that understand the context of images.
- Cognitive systems will create new recipes that appeal to the user’s sense of taste, creating optimized menus for each individual, and automatically adapting to local ingredients.
- Prevented/Predictive Maintenance: Saving companies millions before any breakdown or leaks by predicting and preventing locations and time of such events.
In conclusion, IoT produces a huge amount of data which needs to be interpreted by the AI to meaningful information.
