AIoT: Artificial Intelligence of Things | Bosch Global

Bosch Research boosts trust in and the reliability of AIoT

Shaping the transformation: the use of artificial intelligence within the Internet of Things

In the Internet of Things (IoT), we connect intelligent products and services, generating added value for our customers. By adding AI, we create a closed value creation cycle and focus even more on users. The data resulting from the use of intelligent, connected products and the interaction between people and machines and machines themselves are the key factor in this context. By linking IoT with AI and machine learning, we can draw the right conclusions from huge quantities of data and react to these data during product engineering in seconds. We learn from the data and can thus improve our products and services on an ongoing basis. AIoT makes it possible to develop new products more quickly. At the same time, we can optimize customers’ products during their lifetime for example by using over-the-air updates or we can add new functions.

By using data as a basis for optimizing and personalizing our products, the need for privacy and AIoT security grows. The greater people’s trust in the AIoT, the greater their acceptance. At Bosch Research, we are involved in numerous research projects in order to build this trust.

Our research results in a secure and reliable AIoT

Bosch Research puts in place the technological basis for a more reliable and secure AIoT and thus allows applications and products which are even better geared to customer needs. The focus is always on handling user data in a trusting manner too. After all, customers often ask the following questions when using connected products: How do I keep track of things when dealing with complex processes? How are my data protected against unauthorized access or even manipulation? How is data misuse prevented? Bosch Research takes this seriously, provides answers to questions with technological solutions and products and boosts people’s trust in AIoT:

Develop, connect, improve:the AIoT cycle

The so-called AIoT cycle – a value creation cycle comprising four phases – shows the benefits of linking AI and the IoT:

AIoT: Artificial Intelligence of Things AIoT: the combination of artificial intelligence and the Internet of Things. Bosch Research ensures trust, reliability and security in the AIoT.

Value creation

Connected products provide data. Bosch uses these data during research and development to improve applications and revise or supplement functions. At the same time, we can improve the security and reliability of our products on an ongoing basis and adapt them to meet the individual needs of customers. Making AI in AIoT products secure, robust and explainable is a key issue for us. Research projects such as machine learning testing and AI safety help to achieve this goal.

Products in interaction with customers

We deliver connected products and services to our customers. When these products are used, they generate data, which we use in the following phases of the cycle to improve products and applications. AIoT products ensure greater security for users. Research projects such as embedded AI based siren detection show this.

Data processing

The data which are produced when connected products are used are the basis for this phase of the AIoT cycle. They are collected and stored in a structured manner. With technologies such as self-sovereign identities (SSI) and trustworthy computing , we ensure that users can keep control and maintain sovereignty over their data at all times and that these data are always protected.

AI algorithms

In this phase, we process the data using AI algorithms and machine learning and gain new findings on this basis. The visual analytics research project shows how this process leads to greater security for users: in autonomous vehicles, AI is used for image recognition. In rarely occurring situations where several unusual conditions converge, so-called corner cases, the AI in the image recognition system points out weaknesses. For example when a red traffic light is hard to see from a certain angle in inclement weather. Visual analytics helps to detect blind spots and to automatically supplement the existing data set with the help of a second AI. As a result, shortcomings of the first AI are remedied and overall system accuracy can be increased.

Research Engineer, Dynamic Distributed Systems

Director of Bosch Research and Technology Center in Bangalore, India

VP and Chief Scientist of Integrated Human-Machine Intelligence

Dr. Robert Xie

Head of IoT@Life Program | Group Leader for IoT & I4.0 at Bosch Research and Technology Center in China

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