Cloud computing, Internet of Things, big data, artificial intelligence

        In recent years, cloud computing, Internet of Things, big data, artificial intelligence and other professional terms have become more and more popular words in the information industry and science and technology. These four are closely related, closely related and inseparable. So, what is the relationship between them?

Cloud computing (Cloud)

        Cloud computing is equivalent to the human brain and the nerve center of the Internet of Things. Cloud computing is an add-on, use, and delivery model of Internet-based related services that typically involves providing dynamically scalable and often virtualized resources over the Internet.

        At present, many IoT servers are deployed in the cloud to provide application layer services through cloud computing. Cloud computing can be considered to include the following levels of services: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).


Cloud Computing IaaS: Infrastructure as a Service

      IaaS (Infrastructure-as-a-Service): Infrastructure as a service. Consumers can get services from a complete computer infrastructure over the Internet. For example: hardware server lease.

Cloud Computing PaaS: Platform as a Service

      PaaS (Platform-as-a-Service): Platform as a service. PaaS actually refers to the platform for software development as a service, submitted to users in the SaaS model. Therefore, PaaS is also an application of the SaaS model. However, the emergence of PaaS can accelerate the development of SaaS, especially to speed up the development of SaaS applications. For example: personalized customization of software.

Cloud Computing SaaS: Software as a Service

      SaaS (Software-as-a-Service): Software as a service. It is a model for providing software over the Internet. Instead of purchasing software, users rent Web-based software from providers to manage business operations.

        Amazon is the first company to realize the value of services. It brings the infrastructure, platform and technology that serve the company to the market and provides services to the society. It has become the global cloud computing market leader.

IoT (Internet of things)

        There are two meanings in the connection of things in the Internet of Things: First, the core and foundation of the Internet of Things is still the Internet, an extended and expanded network based on the Internet; Second, the client extends and extends between any item and item. Exchange information and communication. The Internet of Things is an extension of the Internet, enabling informationization, remote management control, and intelligent networks. It includes all resources on the Internet and the Internet, and is compatible with all Internet applications, but all elements of the Internet of Things (devices, resources, communications, etc.) are personalized and privatized. The Internet of Things is an application expansion of the Internet. It is not so much a network entity as a business entity or an application.

The following figure is an example. The Internet of Things is roughly divided into the following levels: the perception layer, the network layer, and the application layer.


        The sensory layer is equivalent to human senses and nerve endings, used to sense and collect various data in the application environment. A variety of sensors including temperature, humidity, speed, position, vibration, pressure, flow, and gas. High sensitivity and accuracy, low power consumption, and wireless transmission are requirements for the sensing layer.

        The network layer is equivalent to the human nervous system and is used to transmit data. Including a variety of wireless communication technologies and standards, such as Zigbee / BLE / Wifi / NFC / RFID / LTE. Low power consumption, wide area coverage, and more connections are the development direction of wireless networks. At present, new communication technologies and standards NB-IoT, LoRa, eLTE-IoT are working in this direction. The future 5G will replace many of the current wireless communication technologies and unify the rivers and lakes.

         The application layer is equivalent to the human brain's indication and response, and the output is controlled in reverse by an instruction. Such as equipment management, environmental monitoring, industrial control, etc.

Big Data (Dig Data)

       Big data is a collection of data that is large enough to capture, manage, and analyze much beyond the capabilities of traditional database software tools. It has a large data size, fast data flow, diverse data types, and low value density.

        Big data analysis is often associated with cloud computing. Big data is not big in terms of data size, but specializes in data and becomes meaningful data. From a technical perspective, big data and cloud computing are like the front and back of coins. Big data must not be processed by a single computer. It must adopt a distributed cloud structure. It is characterized by distributed data mining for massive data, but it must rely on cloud computing distributed processing, distributed database and cloud storage, virtualization technology, Data mining grids, scalable storage systems, and more. If big data is likened to an industry, then the key to profitability in this industry is to increase the “processing power” of the data and “add value” of the data through “processing”.

       The characteristics of big data: 4 "V" - volume, variety, velocity, value, corresponding to the large amount of data; a variety of data types, including the mentioned network logs, video, pictures, geographical information, etc.; processing speed High-value information can be quickly obtained from various types of data; high value density, as long as the data is properly utilized and analyzed correctly and accurately, will bring high value returns.

        From a technical point of view, the relationship between big data and cloud computing is as inseparable as the front and back of a coin. Big data must not be processed by a single computer, and a distributed architecture must be used. It features distributed data mining for massive data. But it must rely on cloud computing for distributed processing, distributed databases and cloud storage, and virtualization technologies.

Artificial Intelligence

        Artificial intelligence makes a metaphor for a person to absorb a large amount of human knowledge (data), and constantly deep learning and evolution into a high person. Artificial intelligence is inseparable from big data, and it is based on cloud computing platform to complete deep learning evolution.

        Artificial Intelligence, abbreviated as AI in English. It is a new technical science that studies and develops theories, methods, techniques, and applications for simulating, extending, and extending human intelligence. Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that responds in a manner similar to human intelligence. Research in this area includes robotics, speech recognition, image recognition, Natural language processing and expert systems.

        From the above point of view, we can simply draw a conclusion: Big data for distributed data mining of massive data must rely on cloud computing distributed processing, distributed database and cloud storage, virtualization technology. Cloud computing is equivalent to the human brain and the nerve center of the Internet of Things. The normal operation of the Internet of Things is to first transmit information to the cloud computing platform through big data transmission, and then artificial intelligence to extract data stored by the cloud computing platform for activities. These four are interdependent and mutually reinforcing. Each technology can only maximize the function with the cooperation of the other three, realize the information-led public security work, the information service public security work, and improve the information application efficiency of the public security organs.

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