Internet of Things in general is no longer at a starting point anymore. You can have a thermostat or internet controlled lights in your house. But what is next? I read the article from Gartner about the adoption of Internet of Things. This adoption is still in the early adopters phase according to their survey.
Nick Jones, vice president and distinguished analyst at Gartner, said, “The IoT demands an extensive range of new technologies and skills that many organizations have yet to master. A recurring theme in the IoT space is the immaturity of technologies and services and of the vendors providing them. Architecting for this immaturity and managing the risk it creates will be a key challenge for organizations exploiting the IoT. In many technology areas, lack of skills will also pose significant challenges.“
Adoption of Internet of Things
A week before Gartner identified the top 10 Internet of Things Technologies that I would like to share with your as well. I selected the 7 most interesting aspects and concerns around the adoption of Internet of Things in the “next step”.
The IoT introduces a wide range of new security risks and challenges to the IoT devices themselves, their platforms and operating systems, their communications, and even the systems to which they’re connected. Security technologies will be required to protect IoT devices and platforms from both information attacks and physical tampering, to encrypt their communications, and to address new challenges such as impersonating “things” or denial-of-sleep attacks that drain batteries. IoT security will be complicated by the fact that many “things” use simple processors and operating systems. Those systems may not support sophisticated security approaches.
IoT business models will exploit the information collected by “things” in many ways. For example, to understand customer behavior and how to deliver services. But also to improve products, and to identify and intercept business moments. However, IoT demands new analytic approaches. New analytic tools and algorithms are needed now, but as data volumes increase through 2021, the needs of the IoT may diverge further from traditional analytics.
IoT Device (Thing) Management
Long-lived nontrivial “things” will require management and monitoring. This includes device monitoring, firmware and software updates, diagnostics, crash analysis and reporting, physical management, and security management. The IoT also brings new problems of scale to the management task. Tools must be capable of managing and monitoring thousands and perhaps even millions of devices.
The processors and architectures used by IoT devices define many of their capabilities, such as whether they are capable of strong security and encryption, power consumption, whether they are sophisticated enough to support an operating system, updatable firmware, and embedded device management agents. As with all hardware design, there are complex trade-offs between features, hardware cost, software cost, software upgradability and so on. As a result, understanding the implications of processor choices will demand deep technical skills.
IoT Operating Systems
Traditional operating systems (OSs) such as Windows and iOS were not designed for IoT applications. They consume too much power, need fast processors, and in some cases, lack features such as guaranteed real-time response. They also have too large a memory footprint for small devices and may not support the chips that IoT developers use. Consequently, a wide range of IoT-specific operating systems has been developed to suit many different hardware footprints and feature needs.
IoT platforms bundle many of the infrastructure components of an IoT system into a single product. The services provided by such platforms fall into three main categories: (1) low-level device control and operations such as communications, device monitoring and management, security, and firmware updates; (2) IoT data acquisition, transformation and management; and (3) IoT application development, including event-driven logic, application programming, visualization, analytics and adapters to connect to enterprise systems.
IoT Standards and Ecosystems
Although ecosystems and standards aren’t precisely technologies, most eventually materialize as application programming interfaces (APIs). Standards and their associated APIs will be essential because IoT devices will need to interoperate and communicate, and many IoT business models will rely on sharing data between multiple devices and organizations.
The adoption of Internet of Things isn’t blocked by technology. It is not completely adopted because of the fact that humans have problems adopting it. A lot of technologies evolve and grow but the people have problems following it. Last but not least if you’re a Gartner client, you can dive deeper into the topic here.