Nuggets Iot software technology is promising

 

The figure shows the IOT architecture.

 

Nowadays, the Internet of Things (IOT) is a popular term. people refer to it as the "artificial skin" on the Earth's surface ". Everyone does not have the same understanding of Iot. In fact, it is no wonder that, after all, the huge coverage of IOT and the ultra-long industrial chain have given us a huge space for imagination. Enterprises in every stage of the industry chain can interpret the Internet of Things from their own standpoint.

However, the industry currently holds that IOT has three conditions: the first is comprehensive perception, that is, making items "speak ", identify and collect item information. The second is reliable transmission, that is, reliable transmission of information through the existing 2g, 3G and 4G communication networks in the future. The third is intelligent processing, which performs Intelligent Analysis and Management through a large background system.

If sensing and communication technologies meet the first two conditions, the third condition must be implemented through software technology. Ye tianchun, director of the Microelectronics Research Institute of the Chinese Emy of sciences, told reporters that at present, China's information network and transmission infrastructure is good, but it is still weak in sensor and chip manufacturing, integration, preprocessing, and other aspects, at the same time, the software technology of massive information processing is also very weak.

Software technology supporting data collection RFID middleware to be broken through

Iot can be divided into three layers: IOT perception layer, Iot network layer, and IOT application layer. The first layer is the perception layer, which is crucial for object perception and data collection. Speaking of data collection, we have to mention RFID (radio frequency identification). Lu centennial, Chief Consultant of sapbusinessobjects China, told China Electronics news that for RFID, hardware vendors can develop their own software, for example, some software is encapsulated in the hardware. On the other hand, software vendors can also provide RF technology. "In the future IOT, apart from software, hardware and software must be fully integrated, including RFID technology. Therefore, the entire market should be very large ." Said Lu centennial.

It is understood that at present, China has already ranked first in the world in the field of high-frequency applications, forming a mature industrial chain from chip design, manufacturing, encapsulation and read/write machine design, manufacturing to application. China's research and application have also stepped up to catch up with the international key ultra-high frequency field. However, the R & D level of RFID Enterprises in China is still relatively weak. "Because the enterprises entering the RFID field are basically small and medium-sized enterprises, their capital strength is relatively weak. In addition, to maintain the operation of enterprises, they cannot invest a lot of money in technology R & D, this greatly limits the technical innovation capability of enterprises." Ouyang Yu, Secretary General of the China RFID Industry Alliance, told the reporter of China Electronic news.

It is understood that in terms of RFID software design, many domestic enterprises have the ability to design closed-loop RFID system software that is currently widely used. In the RFID middleware field, the technical advantages of enterprises such as IBM and Bea are very obvious. Currently, there are no enterprises in China that can compete with them in terms of technical strength.

 

However, the importance of RFID middleware technology cannot be ignored. "Whoever has mastered the middleware technology will be able to have core competitiveness, and who will be able to quickly and cost effectively meet differentiated product requirements. This is also the key to overcome the closed-loop applications of the island type ." Yang Yunping, vice president of Chengdu Jiuzhou electronic information system Co., Ltd., told the reporter of China Electronic news.

Massive information processing improves Bi requirements

Lu Centennial told reporters that the Internet connects machines and people, while Iot connects machines, people, devices, and other things. In the future, people will be able to control air conditioners, televisions, lights, and other household devices in the room through computer terminals, mobile phones, and other handheld terminals, so as to realize smart home. Therefore, in essence, the IOT and Internet ideas are consistent. From this perspective, if the Internet has achieved a large number of software enterprises and technologies, Iot is also a "useful place" for software enterprises and technologies ". At least bi sees market opportunities.

Iot is an intelligent network. In the face of massive data collected, intelligent analysis and processing are required to achieve intelligence. Therefore, business intelligence will be very promising. However, it is precisely because these massive volumes of data have also put forward new requirements for business intelligence:

The first is real-time business intelligence, that is, business intelligence is achieved anytime, anywhere. Affected by internal and external, foreseeable, and unexpected events, any Iot application must analyze and make decisions on the ever-changing environment in real time.

Second, faster analysis. Real-time business intelligence requires faster analysis. This makes business intelligence have to make structural changes. Lu Centennial told reporters that in the past, Bi stored it on the hard disk. Data and hard disk interfaces exchange with each other, which limits the speed improvement. In the past, Bi was just a software. If you want to analyze it, you can connect it to the server through the network for computing. But now, Bi enterprises have not completely solidified the Bi into the hard disk, but are bound with hardware vendors. They have released a tool specifically designed to combine hardware and software for analysis, thus greatly improving the analysis speed.

Again, data quality control. If the authenticity of massive data cannot be guaranteed, wrong results and judgments will be generated, and the consequences will be very serious. Therefore, data quality control is an important guarantee for obtaining real results.

Finally, key performance indicator analysis, real-time query, multi-dimensional analysis, prediction, and easy-to-use data mining are also essential and constantly needed to strengthen bi.