Author: iot101
IoT Think Tank Original
Reprint must indicate source and origin
—— 【Guide】 ——
Today is the second day of the Lunar New Year. Together with the iot101 team, I was reminded to share some light-hearted topics. As always, I respond to requests. I have compiled the top 5 hottest trends in the IoT field, and after reading, you will surely become a well-rounded individual, winning at the start of the new year.
2016 was an exciting year for the Internet of Things (IoT), with nearly every industry investing in IoT.
Currently, B2C consumer products occupy more than half of the IoT market, but according to IDC’s forecast, over 80% of the IoT market will be used for B2B applications by 2020.
In today’s world, various cutting-edge technologies are emerging, forming an era of technological explosion with artificial intelligence, virtual reality, blockchain, and more. With the application of these new technologies, IoT will create new business models, new workflows, and new productivity engines to achieve better cost control and user experience.
Famous Silicon Valley investor Wu Jun said: “2% of people will control the future; either become them or be eliminated.”
The future of IoT belongs to lifelong learners, those who continually update their brain’s “operating system.” By constantly learning and establishing more accurate and clearer concepts, one ensures they remain in a state of continuous growth, ultimately aiming to stay ahead of the majority, such as being ahead of 90% or even 98% of people.
To serve the lifelong learners who follow iot101, I have specially compiled the top 5 trends you need to pay attention to in 2017, released by IBM and Forbes:
Cognitive Computing
Cognitive computing is a brand-new computing model that, through information analysis, natural language processing, and numerous technological innovations in machine learning, can “understand” unstructured data, including language, images, videos, etc., allowing computer systems to learn, think, analyze data, and make correct decisions like the human brain.
What is the difference between cognitive computing and the artificial intelligence we are familiar with? Here is the answer quoted from the Harvard Business Review.
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Scale. Traditional artificial intelligence does not emphasize scale, while cognitive computing must undergo large-scale learning.
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Interactivity. Traditional artificial intelligence dreams of building self-service machines with human intelligence, while cognitive computing focuses on interaction and collaboration with humans.
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Probability. Traditional artificial intelligence dreams of creating precise intelligent machines, while cognitive computing aims to address various unstructured and uncertain data, thus exhibiting a certain level of probability.
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Differences |
Cognitive Computing |
Artificial Intelligence |
|
Characteristics |
Emphasizes cognition and understanding |
Primarily human-controlled, where humans tell machines how to act |
|
Required Abilities |
Has learning and reasoning abilities, can make appropriate decisions through analysis, providing references for people |
Training and cultivation of the recipient |
|
Relationship with Humans |
Interacts with humans and the environment, enhancing human intelligence |
No mutual feedback, primarily human-controlled, working according to human needs |
|
Measurement Standards |
No unique standard, analyze specific problems on a case-by-case basis |
Has measurement standards like the Turing test |
|
Focus Areas |
Big data, especially massive unstructured data |
Simulating humans and the human world |
According to a report by Gartner, the key to generating insights is the ability to interpret unstructured data, which is why cognitive computing is considered the technology needed for the true data age of the future.
With the increasing amount of collected data, cognitive computing enables sensors to automatically diagnose and make decisions without human intervention. Another significant advantage of cognitive IoT is the ability to combine multiple data streams to identify specific patterns and provide more contextual options.
Cognitive IoT combines cognitive computing technology with the data generated by interconnected devices and the operations these devices can perform, creating “thinking” objects.
However, cognitive IoT does not have a fixed program. They learn from interaction with humans and the environment, gradually keeping up with the complexity of IoT and identifying data correlations that are difficult for humans to extract.
IoT Security
Since IoT relies on connectable devices, their security must be considered. All participants in the IoT ecosystem are responsible for the security of their devices, data, and solutions, including device manufacturers, application developers, consumers, and IoT enterprises.
Statistics show that there were 1,117 IoT device vulnerabilities in 2016, affecting manufacturers such as Cisco, Huawei, Google, and Moxa. Among them, traditional network equipment manufacturer Cisco had 356 vulnerabilities, accounting for 32% of all IoT device vulnerabilities for the year; Huawei ranked second with 155; Google ranked third; while industrial equipment manufacturer Moxa and Siemens ranked fourth and fifth. The types of affected devices include network cameras, routers, mobile devices, firewalls, gateway devices, switches, etc.
Types of IoT device vulnerabilities include privilege escalation, denial of service, information leakage, cross-site scripting, command execution, buffer overflow, SQL injection, weak passwords, design flaws, and more. Among these, privilege escalation, denial of service, and information leakage vulnerabilities ranked the top three, accounting for 23%, 19%, and 13% of the total recorded vulnerabilities, respectively.
The security of IoT requires a multi-layered methodology. From the device’s perspective, security should be prioritized from the initial design and development stage, and the safety of hardware, software, and data must be maintained throughout the device’s lifecycle.
To fully realize the potential of IoT, security challenges must be addressed through interoperability and well-designed access controls. When designing security features, a proactive approach should be taken rather than a passive one, developing better products and solutions.
Blockchain IoT
Blockchain can enhance security, make transactions more seamless, establish trust, reduce costs, and accelerate transactions, thereby improving supply chain efficiency and playing an important role in IoT.
The idea of applying blockchain technology to the IoT field has existed for some time. In fact, blockchain technology appears to be a suitable solution for at least three aspects of IoT: big data management, security and transparency, as well as the convenience brought by microtransactions based on the exchange of services between interconnected smart devices.
IoT is essentially connected to big data. As the number of installed IoT units continues to increase, the data collected on consumer habits and behavior patterns in the IoT is multiplying. How to process this vast amount of data has become a problem that must be solved. In this case, some believe that “the only option is to use blockchain technology, and there is no alternative.”
Blockchain technology can not only provide a suitable solution for recording all data from IoT units but also ensure that once data is recorded, it cannot be changed thereafter. Therefore, co-author of the book “Blockchain Revolution: How the Technology Behind Bitcoin is Changing Money, Business, and the World,” Alex Tapscott, stated:
“IoT needs a Ledger of Things, which needs to record everything happening within the IoT, including conversations, who owes whom money, etc., and coordinate everything that happens.”
Currently, blockchain IoT has already been adopted by some companies. The Dutch company Kinno has connected its devices to the blockchain, developing a solution that can track, monitor, and report the status, location, and optimal packaging and shipping routes of containers.
Another example is Tilepay, which provides a payment solution for the existing IoT industry, either person-to-machine or machine-to-machine. Tilepay is a decentralized payment system based on blockchain, which can be downloaded and installed on a personal computer, laptop, tablet, or smartphone. All IoT designs will have a unique token used to receive payments through blockchain technology. Tilepay will also establish a data trading market for IoT, allowing everyone to purchase data from various devices and sensors in the IoT.
API (Application Programming Interface)
APIs are used to connect information and rich data to the IoT, enhancing the practicality of IoT. The importance of APIs for IoT is self-evident, yet how to monetize IoT APIs is a problem that must be faced sooner or later.
Currently, there are several methods for monetizing IoT APIs:
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Temporarily free: Use free APIs to attract developers to create related applications. Once the number of application users increases, developers may pay for more resources. You can also request a share from the purchases made by users from the applications, a strategy employed by both Apple and Google.
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Direct charging: You can charge per account or based on usage. It is advisable to set a payment threshold when charging based on usage, so that after reaching a certain amount, payment must be made to continue using to avoid uncollectible debts.
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Micro-payments: This is a relatively new concept that has particular practical significance for IoT. With the emergence of connected cars, there can be many different methods of payment in parking lots and toll booths.
The innovative applications of APIs are gradually emerging. For example, OMsignal integrates sensors into ordinary clothing to monitor heart rate, breathing, exercise intensity, and calories burned, and opens APIs and SDKs for software manufacturers to develop different types of applications. Clearly, this wearable form is likely to be more acceptable to people.
IoT Platforms
The IoT platform has been brewing since the day IoT was born, as those who control the platform hold the key to success, and everyone wants to seize it. As stated in the IoT Analytics report, competition is fierce, with the number of IoT platform providers exceeding 400. Cisco made headlines in February by acquiring platform provider Jasper for $1.4 billion.
IoT platforms must be able to connect devices, collect data, process thousands of suppliers, bridge dozens of standards, and support millions of devices, processing billions of pieces of information. To realize the super value of the platform, it must also add cognitive computing, IoT security, privacy protection, and decision-making capabilities.
The recently released report “Forrester Wave: IoT Software Platforms (Q4 2016)” analyzed existing IoT platforms. The survey shows that IBM, PTC, GE, and Microsoft have become the dominant players in the IoT platform market. SAP, AWS, Cisco, LogMeln, Exosite, Ayla Networks, and Zebra Technologies are among the top 11.
By the end of 2016, The giants in the cloud computing field of IoT have shifted their focus to fog computing and edge computing. Microsoft provided support for its serverless event-driven platform Azure Functions in the Azure IoT Gateway SDK, offering cloud-based scalability for developers building IoT solutions on Azure. Amazon announced that AWS Greengrass could support Lambda Functions for IoT devices. Google launched a developer preview version of its new IoT platform, Android Things.
These are the top 5 trends in IoT for 2017 compiled by iot101.
The development of IoT is so rapid that new things are constantly emerging.
May you be well-prepared in advance.
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