A good 'smart sensor' is a microprocessor-driven suite of sensors and instruments with communication and onboard diagnostics capabilities. Smart sensors can store various detected physical quantities and process this data according to instructions, thereby creating new data. Smart sensors can exchange information and autonomously decide which data to transmit, discard abnormal data, and perform analysis and statistical calculations.
Smart sensors, simply put, combine artificial intelligence with sensor technology, resulting in a product of the symbiotic evolution of hardware and software. In the future, there will be 50 billion interconnected devices. Most of these devices will be equipped with sensors, perhaps embedded in ElectricImp or externally connected via Estimote. These sensors will generate unprecedented amounts of data.
Artificial intelligence technologies can benefit sensor systems, including knowledge-based systems, fuzzy logic, automated knowledge collection, neural networks, genetic algorithms, case-based reasoning, and environmental intelligence. These technologies are increasingly used in sensor systems, not only because they are effective, but also because of the growing prevalence of computer applications today.
These artificial intelligence technologies have minimal computational complexity and can be applied to small sensor systems, single sensors, or systems using low-capacity microcontroller arrays. The proper application of artificial intelligence technologies will create more competitive sensor systems and applications.
Other technological advancements in artificial intelligence will also impact sensor systems, including data mining, multi-agent systems, and distributed self-organizing systems. Environmental sensing technology can integrate numerous microelectronic processors and sensors into everyday objects, imbuing them with intelligence. These can create intelligent environments, communicate with other intelligent devices, and interact with humans. The suggestions provided can help users complete tasks more intuitively, but the consequences of this integration will be difficult to predict. Utilizing a combination of environmental intelligence and multiple artificial intelligence technologies can maximize the potential of this technology.
Artificial intelligence (AI) is being used to optimize sensor systems. Emerging in the 1950s as a branch of computer science, AI has spawned many powerful tools that play a significant role in sensor systems, automatically solving problems that previously required human intelligence.
While the integration of artificial intelligence into industry has been slow, it will inevitably bring advancements in flexibility, reconfigurability, and reliability. New systems are increasingly demonstrating performance exceeding human capabilities in a growing number of tasks. As they become more integrated with human capabilities, we are combining the human brain with computing power to enable discussion, analysis, reasoning, communication, and invention.
Artificial intelligence (AI) combines various advanced technologies, endowing them with the capabilities of machine learning, adoption, and decision-making, giving them entirely new functionalities. This achievement relies on technologies such as neural networks, expert systems, self-organizing systems, fuzzy logic, and genetic algorithms. AI technology has expanded its application areas to many other fields, some of which require the analysis and processing of sensor information, such as assembly, biosensors, building modeling, computer vision, cutting tool diagnostics, environmental engineering, force sensing, health monitoring, human-computer interaction, network applications, laser milling, maintenance and inspection, power assistance, robotics, sensor networks, and remote operation, among others.
These advancements in artificial intelligence have been incorporated into more complex sensor systems. A click of a mouse, a tap of a switch, or even a thought can transform sensor data into information and send it to you.
