Driven by big data, cloud computing and artificial intelligence, the Internet of Things has undergone certain changes, which are mainly reflected in three aspects. One is the Internet of Things platform; the second is data analysis; and the third is application. Among them, the Internet of Things platform involves cloud computing technology, data analysis involves big data technology, and applications mainly refer to artificial intelligence technology. Artificial intelligence is currently at the highest level of the Internet of Things system. Not only do the major technologies ultimately point to artificial intelligence, but artificial intelligence is also the key to the great value of the Internet of Things. It can be said that the interconnection of all things requires the intelligence of all things.
The combination of the Internet of Things and artificial intelligence is the inevitable result of their development. The Internet of Things needs to play a greater role through artificial intelligence in order to expand the application boundaries of the Internet of Things. This is also one of the core demands of the development of the Industrial Internet. And artificial intelligence also needs the important platform of the Internet of Things to complete landing applications.
As artificial intelligence and the Internet of Things become more and more widely used, it is necessary to understand how these two technologies work together to benefit enterprises and ordinary people.
IoT devices generate large amounts of data, and artificial intelligence and machine learning can be used to analyze and track this data. Combining artificial intelligence with the Internet of Things in this way can create “smart devices” that can make smart decisions without human intervention. The possibilities brought by the Internet of Things are limitless.
The rapid expansion of networked devices and sensors will cause the amount of data they create to grow exponentially, and the biggest problem that comes with it is how to analyze these massive performance data.
The only way to keep up with the speed at which the Internet of Things generates data and gain insights is machine learning.
What is artificial intelligence and what is machine learning?
Artificial intelligence is the study of agents that perceive the world around them, form plans, and make decisions to achieve goals. Its foundation includes mathematics, logic, philosophy, probability theory, linguistics, neuroscience and decision theory. Many fields fall into the category of artificial intelligence, such as computer vision, robotics, machine learning, and natural language processing.
Machine learning is a branch of artificial intelligence, and its goal is to allow computers to learn by themselves. The machine’s learning algorithm enables it to recognize patterns in data, then build models that explain the world, and predict things without clear pre-programmed rules and models.
Why is machine learning important?
Artificial intelligence will be more capable of shaping our future than other innovations, and anyone who does not understand it will soon find themselves left behind.
After many artificial intelligence winters and “false prosperity”, the rapid development of data storage and computer processing capabilities has greatly changed the rules of the game.
Machine learning has made tremendous improvements in computer vision (the ability of machines to recognize objects in images or videos). For example, if you collect hundreds of thousands or even millions of pictures, you need to label them separately. For example, you want to label pictures with cats. Then, the algorithm tries to build a model that can accurately give a picture of a cat that is labeled. Once the accuracy is high enough, the machine can “understand” what the cat looks like.
The realization of the Internet of Things relies on being able to gain insights hidden in a vast and growing ocean of data. Since the current method cannot be extended to the scale of the Internet of Things, the promised future of the Internet of Things depends on machine learning to discover patterns, correlations and anomalies, and these patterns, correlations and anomalies may improve all of our daily lives aspect.
Machine learning is at the core of our journey towards artificial intelligence. At the same time, it will change every industry and have a huge impact on our daily lives.
The key to success of IoT artificial intelligence
1. Focus on a challenge
Although it is easy for people to be excited that the Internet of Things and artificial intelligence can solve all the challenges, this is a misunderstanding. Focusing on a problem or inefficiency related to a particular process will enable your organization to develop a realistic strategy to allocate the right resources and collect only the data needed. Don’t try to solve all problems. By responding to major organizational challenges and showing early success stories, management’s confidence and commitment to the plan will be enhanced. Once you have selected the process to be improved, you first need to analyze it from several perspectives, such as input/output, time value, financial value, and other indicators to determine the next steps and the data to be collected.
2. Iterate indefinitely
There is no “set in stone” IoT/artificial intelligence platform. This is a commitment to continuous improvement. Finding and refining value in data is like finding the perfect gem. You can deploy sensors first to get preliminary insights. This may require different perspectives to discover patterns-time interval, geographic location, demographics, etc. Sometimes this means developing new algorithms to “test” different patterns. As the insights become clearer, you need to optimize these algorithms and start moving them closer to the digital edge of data generation and use. As you continue to refine your findings with predictive analytics and machine learning algorithms, the path to value will become clearer.
The Internet of Things is actually not a new concept, but why the Internet of Things can still be included in the core technology of the third wave of informatization along with big data and cloud computing technology. A key reason is that the Internet of Things can carry more new technologies. At the same time, the Internet of Things can penetrate into the industrial field.
The Internet of Things will gain important support. Various innovative applications based on the Internet of Things will become a hot spot for a new round of entrepreneurship. An important feature of these new innovative fields is the deep integration of the Internet of Things and artificial intelligence. The deep integration of the Internet of Things and artificial intelligence will be widely used in fields such as smart cities, industrial Internet of things, smart homes, agricultural Internet of things and various wearable devices, and these fields undoubtedly have huge development potential.
Faced with today’s rapid development of IoT, AI and other new technologies, whether it is a government, a company or an individual, only by fully recognizing the general trend of human development that it has triggered, and constantly adjusting its value concept, operation mode, etc., can it be fully effective by taking advantage of the trend. Continuous technological innovation is the way of development, and it can promote the Internet of Things to contribute to the universal sharing of human society.