the IOT application cases with the help of AI in the near future

Artificial intelligence helps machines to behave like humans in areas like face recognition, decision making, learning and solving problems. AI are basically used for learning and taking self-decisions on the processing of complex organized or unorganized data. This technology has revolutionized the digital world like the smartphones did.

IoT and Machine Learning

We can call IoT as the data “supplier” while machine learning as data “miner.” First step is refining before IoT work supply data. There are a lot of IoT sensors and external factors which produces millions of data points. It is the task of the “miner” or machine learning to identify correlations between them, extract meaningful insight from these variables and transport it to the storage for further analysis. The traditional analytical approach to data includes the system gathering past data and produce reports and results based on data processing. IoT and machine learning works more on prediction. It starts with the desired outcome and searches interactions between input variables to meet the criteria.

Another advantage of applying machine learning to IoT data is in the ability to automatically improve its algorithms. As more data are being available now, a smart system returns even more accurate predictions due to its smart thinking. In this way, businesses can conclude to a perfect decision without actual “thinking.” Or human interaction. The artificial system has answers to every aspect, starting from the machine safety or power reduction to the increased supply of personalized goods and services.

AI in IoT applications

In IoT applications,  you require machine learning to face various situations. When a device detects unusual conditions due to any error, it needs to know how to and when to react or whether to respond autonomously or whether it need human assistance. Definitely it requires intelligent learning and decision-making capabilities to make such wise decisions. Google uses this approach in the RankBrain algorithm. It actually requires deep learning to guess the meaning of an error. Once you get the solution, it responds in real-time without any human intervention.

1.Boosting efficiency

With the help of predictive analytics, machine learning with AI learns from the data to decipher trends and make predictions about future events. This unlocks the real benefits of IoT in a variety of manufacturing industries.

2.Healthcare

In the healthcare sector, AI together with IoT network can improve patient care. Sensors from medical devices such as healthcare mobile apps, fitness trackers and digital medical records have been producing and storing patient’s data. The AI and IoT approach can help predict diseases, suggest preventive maintenance, track physical activity, heart rate, body mass, temperature and provide drug administration by reviewing the medical history and identifying the health problem. When it is regarding health protection or disease control, patients and doctors would accept the benefits that come with the AI and IoT approach.

3.Forecasting

Accurate forecasts help farmers to plan optimal days for farming or harvesting. Train or plane schedules fully depends on weather forecasting to modify for expected weather interruptions. Businesses that are weather dependent,can accurately employ labor and resources according to expected weather events. Here comes the role of artificial intelligence. AI can help make more accurate forecasting. Artificial intelligence (AI) techniques apply its method on past predictions and actual outcomes. By comparing predictions with outcomes, there is improvement of simulation capabilities. It results in much better forecasting for the future, with greater accuracy. It feeds data into algorithms that literally require both quality and quantity. This is done in order to be effective at past occurrences with future predictions.

4.Scalability

IoT can scale data. What does it mean? Connected devices ranging from high end computer system to sensors share data among themselves. Here AI plays the role of extracting information from one device. Before transferring it to other, it analyses and summarizes the data. Thus it reduces the enormous amount of data to a suitable amount. This is called scalability.