Looking to the future_what is the next step of the Internet of Things
In the past few years, the number of devices connected through the Internet of Things (IoT) has grown exponentially and will continue to grow. It is expected that by 2020, 50 billion connected devices will exist, thanks to many new smart devices that have become the standard tools for people and businesses to manage many daily work and lives.
Smart connected devices increase customer engagement, improve visibility and simplify communication, especially the use of new human-machine interfaces, such as Voice User Interface (Voice User Interface, VUI).
In the future, the Internet of Things will continue to develop at a very rapid rate and succeed in many ways. The ultimate goal is to have an intelligent and completely secure IoT system, however, many obstacles need to be overcome before the goal can be achieved.
IoT and blockchain integration
The current centralized network structure of the Internet of Things is one of the main reasons for the vulnerability of the Internet of Things. As billions of devices are connected and more devices are added, the Internet of Things has become an important target for cyber attacks, which makes security very important.
Blockchain brings new hope for the security of the Internet of Things for several reasons: First, the blockchain is public, and everyone involved in the network of blockchain network nodes can see the storage and approval of blocks and transactions , Although users can still have private keys to control transactions; secondly, blockchain is decentralized, so there is no single authority that can approve transactions that eliminate single points of failure (SPOF); third, and most importantly, it is Safe, the database can only be expanded, and previous records cannot be changed.
In the next few years, manufacturers will recognize that blockchain technology is embedded in all devices and compete for the benefits of "Blockchain certification."
IoT investment is increasing
The influence of the Internet of Things has and will continue to attract more start-up venture capitalists to participate in innovative projects in the fields of hardware, software and services. According to data from International Data Corporation (IDC), by 2021, IoT spending will reach 1.4 trillion dollars.
The Internet of Things is one of the few markets that interest traditional venture capitalists. The popularity of smart devices has increased the customer's dependence on using them to perform daily tasks, which will increase the enthusiasm for investing in IoT startups. Customers will wait for the next major innovation of the Internet of Things, such as smart mirrors, these mirrors will analyze your face, it will tell you if you look sick; smart ATM machine, it will contain smart security cameras; smart forks, Can tell you how to eat, what to eat; and smart bed, when everyone sleeps, the lights will be turned off.
Fog computing and Internet of Things
Fog computing is a technology that distributes processing load and moves it to the edge (sensor) of the network. The benefits of using fog computing are very attractive to IoT solution providers. Some of these advantages allow users to minimize latency, save network bandwidth, collect and protect various data through rapid decision-making and reliable operation, and transfer data to the optimal processing location through better analysis and insights on local data. Microsoft has just announced an investment of 5 billion US dollars to invest in the Internet of Things, including fog / edge computing.
AI and IoT will work closely
AI will help IoT data analysis in the following areas: data preparation, data discovery, visualization of streaming data, time series accuracy of data, prediction and advanced analysis, and real-time geospatial and location. Here are some examples:
Data preparation: Define the data pool and clean it up, which will allow us to understand concepts such as Dark Data and Data Lakes.
Data discovery: Find useful data in a defined data pool.
Visualization of streaming data: By defining, discovering data and visually processing streaming data in an intelligent manner, the decision-making process can be carried out without delay.
Accuracy of time series data: keep the data highly accurate and complete, and the data highly reliable.
Predictive and advanced analysis: make decisions based on collected, discovered, and analyzed data.
Real-time geospatial and geographic location (logistics data): Keep data flowing and under control.
Standardization battle will continue
Standardization is one of the biggest challenges facing the development of the Internet of Things. This is a battle between industry leaders competing for the market in the early stages. Digital assistant devices including HomePod, Alexa, and Google Assistant are the future hubs of smart devices in the next stage. Companies are trying to establish "their hubs" with consumers to make it easier for them to use fewer devices Practical network.
But what we are seeing is a fragmented status quo, and there is no organization like IEEE or government regulations that strongly promotes universal standards for IoT devices.
One possible solution is that a small number of devices dominate the market, allowing customers to choose a device and allow the use of any other connected device. Similar to the Windows, Mac, and Linux operating systems we have today, there is no cross-platform standard.
To understand the difficulty of standardization, we need to deal with all three categories in the standardization process: platforms, connectivity, and applications. As far as the platform is concerned, we deal with UX / UI and analysis tools. Connectivity needs to deal with the point of contact between the customer and the device. Finally, applications are interoperable applications that control, collect, and analyze data.
All three categories are interrelated and we all need them. The lack of one will break this model and delay the standardization process.
IoT talent shortage
The demand for IoT talent is rising, including the growing demand for talents with artificial intelligence, big data analysis and blockchain skills.
The university cannot keep up with the demand. In order to cope with this shortage, the company has developed an internal training plan to build its own team, improve the capabilities of its engineering team, and cultivate new talents.
Speakers are one of the most common output devices used with computer systems. Some speakers are designed to work specifically with computers, while others can be hooked up to any type of sound system. Regardless of their design, the purpose of speakers is to produce audio output that can be heard by the listener.
Speakers are transducers that convert electromagnetic waves into sound waves. The speakers receive audio input from a device such as a computer or an audio receiver. This input may be either in analog or digital form. Analog speakers simply amplify the analog electromagnetic waves into sound waves. Since sound waves are produced in analog form, digital speakers must first convert the digital input to an analog signal, then generate the sound waves.
The sound produced by speakers is defined by frequency and amplitude. The frequency determines how high or low the pitch of the sound is. For example, a soprano singer's voice produces high frequency sound waves, while a bass guitar or kick drum generates sounds in the low frequency range. A speaker system's ability to accurately reproduce sound frequencies is a good indicator of how clear the audio will be. Many speakers include multiple speaker cones for different frequency ranges, which helps produce more accurate sounds for each range. Two-way speakers typically have a tweeter and a mid-range speaker, while three-way speakers have a tweeter, mid-range speaker, and subwoofer.
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