6 Core IoT Technologies that You Must Know!
Most of us understand IoT as setting up a wireless-capable device, connecting it to the cloud, and finally collecting data over time. While that’s definitely accurate as a basic understanding, did you know that there are more core IoT technologies that are greatly important for effective IoT? In this article, I’ll share with you 6 types of core IoT technologies that you definitely should know about!
The Challenges of IoT
The Internet of Things describes a network of interconnected “things” or electronic devices that are equipped with sensors and computing capabilities and can communicate with one another. These devices are embedded in a great variety of edge applications, such as modern smartphones, industrial monitoring and control systems, or autonomous vehicles.
As the uses of IoT become more advanced, however, the requirements for their usage become more strict. For instance, industrial control systems that begin to incorporate IoT technologies need these additions to be reliable for continuous operations, or businesses may be put at risk of disruption and significant revenue loss. Thus, unique technologies become necessary to bolster real-world IoT implementations.
That said, it is precisely the core IoT technologies we will discuss today which will aim to overcome such challenges to make IoT safer, faster, and more practical to implement for such unique use cases. Without further ado, let’s dive right in!
1. Multimedia IoT
Multimedia in IoT refers to IoT Applications that involve the use of graphics, media, video, vision and imaging data for insights on the edge. For example, this might include cloud-based point of sale (POS) in retail, network video recorders for surveillance in smart cities, human machine interfaces in industries and even in medical imaging. Such applications typically run on specific hardware to accelerate multimedia decoding and encoding, in order to provide fluid services and user experiences in real time.
2. Edge AI
Multimedia in IoT also builds the foundation for computer vision and vision analytics, which is a subset of Edge AI. Edge AI uses machine learning models on the edge to provide intelligent insights in real time. Some popular examples that you might be aware of are vision-based quality control in industries, real-time road traffic management in smart cities, medical imaging diagnostics, real-time predictive analytics etc. These possibilities in IoT are enabling a new age of automation technologies that are projected to drastically improve both industrial productivity and safety in the next decade.
However, machine learning models do require some computing power to run properly, especially with the complexity of covolutional or recurrent neural networks that we have today. Thus, using GPUs or specialised hardware for edge ML such as deep learning accelerators can drastically improve the effectiveness of your edge AI solutions.
3. Real-Time Computing
IoT systems work in dynamic environments and are required to perform real-time computing and deliver outputs in real time – think of aviation, transportation, robotics, industrial automation, for example, where even a split second can make a drastic difference.
These IoT applications are what we term as “time sensitive”, meaning that data delivery and network communications both within and between devices need to occur in a timely manner with pre-defined latencies, so that the computing tasks as a whole are completed within an acceptable time frame and in an optimised manner.
Efforts to achieve effective Real-Time Computing include standards such as Time Sensitive Networking (TSN) for deterministic networking, as well as hardware like Intel’s Time Coordinated Computing (TCC) technologies that optimise and allocate computing resources for timely computing. To learn more about TSN and Intel TCC, be sure to visit my previous article here.
4. Functional Safety (Industrial Safety)
IoT devices are also being heavily used to enhance safety in industrial settings with what is known as functional safety. Functional safety refers to the use of active systems as fail-safes that guard against electronic failures or human error. One common feature implemented for functional safety might be the automatic deactivation of industrial machinery if anomalous performance metrics are detected.
There are also many other ways to use IoT for improving industrial safety. Read about 9 ways to do so in my previous article!
5. IoT Security
Given the distributed yet interconnected nature of IoT systems, individual devices can become points of vulnerability if not sufficiently protected with security measures. Cyber-attacks on single devices can then spread quickly throughout the network with existing connections, which may cause significant disruption to the system or worse – disable it entirely.
IoT security is an extremely important and relevant field of development that explores the protection of devices, network connections, and the data they transmit. Such measures include hardware such as cryptographic chips or software like encrypted communication protocols. To learn more about securing your IoT systems, read my previous article where I talk about various ways to achieve IoT security in detail!
6. IoT Manageability
State of the art IoT systems can carry as many as thousands of devices and an exponentially larger number of connections in a single network. As solutions continue to scale, monitoring, accessing and maintaining devices can be a significant challenge. Thus, IoT manageability is an extremely important aspect to consider.
IoT manageability features at scale allow you to easily manage your systems by not only monitoring device health, but also to remotely access, update or recover them. This improves manual management processes by lowering costs and increasing productivity. With better access, security updates can also be delivered in a timely manner to further enhance the security of IoT systems.
Design Holistic IoT Solutions with reServer
If you want to design a holistic IoT solution that encompasses those 6 core IoT technologies that I’ve shared today, have a look at reServer. reServer is a compact yet powerful server solution that can be applied to a variety of IoT applications. It is powered by Intel’s latest 11th Gen Intel Core Tiger Lake processor, which carries the latest Intel Xe Graphics for advanced multimedia processing and Intel Deep Learning Boost – specialised hardware for running machine learning.
Furthermore, the higher end reServer versions that run on the Intel i5 1145GRE and i7 1185GRE processors carry Intel TCC technology and TSN for meeting real time computing needs. They also feature compatibility with the Intel vPro platform, which allows you to take advantage of enterprise grade remote manageability features!
Not only that, reServer comes with diverse network connectivity capabilities, including two high-speed 2.5-Gigabit Ethernet ports and hybrid connectivity with 5G LoRaWAN, BLE and WiFi – as well as integrated cooling and dual SATA III connectors for internally mounting 3.5” SATA hard disk drives. A true all-in-one package!
- CPU: Latest 11th Gen Intel® Core™ i3 CPU running up to 4.10GHz (Base)
- Graphics: Intel UHD Graphics Xe G4 48EUs running up to 1.25 GHz (Base)
- Rich Peripherals: Dual 2.5-Gigabit Ethernet, USB 3.0 Type-A, USB 2.0 Type-A, HDMI and DP output
- Hybrid connectivity including 5G, LoRa, BLE and WiFi (Additional Modules required for 5G and LoRa)
- Dual SATA III 6.0 Gbps data connectors for 3.5” SATA hard disk drives with sufficient internal enclosure storage space
- M.2 B-Key/ M-Key/ E-Key for expandability with SSDs or 4G and 5G modules
- Compact server design, with an overall dimension of 124mm*132mm*233mm
- Quiet cooling fan with a large VC heat sink for excellent heat dissipation
- Easy to install, upgrade and maintain with ease of access to the internal components
Don’t wait, learn more on the Seeed Online Store!
Summary & More Resources
In this article we discussed 6 core IoT technologies that are directed towards addressing specific challenges and enhancing use cases for connected devices on the edge. As we’ve discussed, the concept of IoT appears deceptively simple at first glance – in reality, there are many factors that determine the success of a solution’s actual implementation, so we may very well see even newer fields and technologies emerge with time. After all, that is indeed the exciting nature of edge computing in dynamic environments!
Check out our other articles to learn more about IoT, edge computing, and edge computing solutions!