There is no doubt that business models currently have three major trends: the Internet of things (IoT), big data and artificial intelligence (AI). From the still dispersed Internet to the rapid fluctuations in the computing paradigm, how people reshape our lifestyle, everyone is talking about these trends, but what really happened?

The following is your understanding of consumer demand and the future of the future from a consumer perspective.

Big data

The large data defined in Wikipedia is the term for a data set that is so large or complex that traditional data processing applications are insufficient to handle them. As the data set is very large, the challenges faced include capture, storage, analysis, data management, search, sharing, transmission, visualization, query, update, and information privacy. However, it is more likely to be used for reference, predictive analysis, user behavior analysis, advanced data methods (including artificial intelligence), and not just data set sizes.

In 2017, the expectation of the advent of block technology applications, especially in the ledger systems, was made of an intelligent contract written in code. These are often safer and irreversible than traditional contracts, but improve efficiency when quoting and executing them.

In addition, the rise of data self-service solutions will allow organizations to analyze their data without having to build a data science division. For small and medium-sized enterprises without budget, it is very valuable for high demand data scientists in 2016.

The use of Hadoop has also declined rapidly, and this framework allows for distributed processing of large data sets, because the hiring of the necessary talent to support the framework proved to be challenging inside. It also prefers to use applications on the cloud to reduce data center spending, thereby making the data self-service model popular.

As the research firm Gartner Inc. in the analysis of data management, points out the Magic Quadrant scheme because of its flexibility, agility and operational pricing model, is now expected to cloud deployment options as an alternative.

Therefore, since more companies are able to provide employees with the right knowledge from structured and unstructured data, you can expect C managers to gain insight more easily.

This is a double-edged sword, but with the development of big data technology, executives' expectations will become their data immediately, rather than waiting for batch analysis reports. As a result, near real-time data provides faster analytical pressure.

Internet of things

Forbes describes the Internet of things as the concept of connecting any device (and / or each other) that has switches on and off. If the device has a switch, it may be configured as part of the IoT.

Think of "smart home" devices such as locks that can be unlocked when they detect near your phone, or may be turned on lights when detected when moving.

In 2016, we saw the noise from many suppliers with similar solutions. In 2017, we can expect some of these suppliers to win, which will result in fewer suppliers on the market. As vendors decrease, we can also expect regulation and standardization to play a role in making us simpler and more cohesive solutions. At the same time, it was a security issue, as the IoT attacks last year took up a grid in the west of Ukraine. Of course, the study of self drive by car hackers has also aroused concern, so 2017 may bring security measures to the Internet of things.

Now, we encountered a lot of networking market is dispersed in the matter, but I hope that with the development of the rest of the time in 2017, will IOT solutions more perfect, but also a part of the ecological system and the open platform will promote interoperability and combination of data to provide services from multiple sources and equipment.

Two major areas of application may become the focus of the Internet of things, namely smart city and smart home. However, in the smart home division, as the bandwidth is a prerequisite for any IoT technology work, it is expected that the wave of network management grid or similar mesh products will be simpler this year.

That's what Errett Kroeter, the vice president of marketing for Nonprofit Bluetooth special interest groups, brands and developers, wants. "At present, some other standards for meshing are notoriously difficult. Our goal is to preserve the simplicity of the mesh network so that people actually want to use them. "

Finally, the development of the Internet of things, combined with other devices and systems that generate large amounts of data, is accelerating the demand for artificial intelligence, creating meaning from this information

Artificial intelligence

The dictionary definition of artificial intelligence is the ability of machines to simulate intelligent human behavior. Although our recovery in 2016 has been a big increase in AI, but we will further increase in 2017. Back in 2016, we learned that Amazon's Alexa, which exhibits artificial intelligence in the form of human language, is now in more than 5 million homes. You can ask Alexa about the weather or tell her to ask you for a taxi, and she will respond. This means that last year, AI entered the mainstream adoption.

However, there are still many developments in the artificial intelligence in the medical industry. The focus of smartphone start-ups grew from 20 in 2012 to nearly 70 in 2016. Obviously, the key note is iCarbonX, the ecological system aims to build a digital life, health system and Flatiron Health management to achieve personalized, aims to organized data against cancer, oncologists to help improve the quality of nursing care.

In health technology giant PHILPS, at present, there are about sixty percent researchers, developers and software engineers are dedicated to the field of medical informatics innovation, most researchers are working on artificial intelligence application in current and future medical innovation.

Trends in health care, artificial intelligence applications focus on imaging and diagnosis, and artificial intelligence can help you discover subtle details and changes in images that people can't see. This is becoming a crowded industry. It also helps to prevent healthy populations and people in danger, and the deterioration of the health of chronic disease patients using large data sets is a key area.

Jeroen Tas, chief innovation and strategy officer at PHILPS, believes that AI helps radiologists prepare information about cases and identifies subtle changes in the patient's condition. Another area is the intensive care unit, which can help identify early signs of an acute attack, such as sudden cardiac arrest or sudden death.

Tas also claims that by creating genetic information with pathology, medical images, laboratory results, family history, other conditions, and previous treatments, a richer picture of the patient can be created. These data can be organized with the help of AI to increase the important additional context and help clinicians to make more accurate diagnosis and support personalized treatment options.

The multidisciplinary team of software engineers, designers, and other experts seems to have created and introduced the first validated application for radiologists. In the remote patient monitoring, artificial intelligence can realize virtual nursing, including virtual nursing assistants

2017 and beyond

The Internet of things, big data and human resources are growing and approaching more commercial and public use cases.

As they move into their normal and everyday lives, the three trends will become interrelated to provide a more powerful, smoother product.