Challenges Facing IoT Systems in 2019

Challenges Facing IoT Systems in 2019

There is no doubt that we have made significant progress in many key components of IoT systems, in recent years. These developments have in fact made IoT possible. Computer hardware has come down in cost, size and price. For many the Raspberry Pi and other similar devices has facilitated the ability to experiment and innovate, this coupled with the huge open-source community that has provided operating systems and tools that unlock these devices.  

Mobile and other communication networks have improved driven by the demand from initially mobile phone users. This has also driven the development of mobile devices, which has driven improvements in batteries, screens, sensors and the entire software eco-system that runs on these devices. 

With all this development, there are still a number of significant challenges. In order to roll out significant quantities of IoT devices, there are opportunities to improve deployment solutions. we live in a world of orchestrated containers, whilst this has created significant progress in terms of continuous deployment these technologies are network intensive and will require further refinement to work in a performant way in an IoT context. Engineers in IoT face similar challenges to those who tackled the large data scale issues 10 years ago, however with more constraints. 

The logistics of deploying large volumes of sensors is prohibitive and hence dynamic software updates are almost mandatory.  

With the vast number of devices deployed, dynamic updates and the importance of the systems that become reliant on this data, security becomes a big concern. We need mechanisms that ensure data validity and authenticity in a way that is effective and performant.

Bandwidth is improving, but this is being consumed by the volume and the number of applications for IoT data. Hence bandwidth remains and will possibly always remain a constraint. 

With the proliferation of devices, we have challenges around processing this data. Technology is emerging that can capture and process huge volumes of data, however, the technology and tooling around these technologies requires further development. 

Hanging off all this data gathering, we are developing data models and machine learning models, there are significant challenges deploying these models. In many cases, we have sensor data, which need to be processed, this along with more static data, such as location, geographical, weather or other data.

Along with all of the above, we need systems to monitor the entire network. In many cases we cannot consider the IoT devices as "Edge" devices, rather they are becoming "part" of the network, and as such need a sufficient level of monitoring to ensure that the overall system remains reliable and stable.

Whilst IoT has certainly opened up the realms of possibility, it brings with it new challenges that we are yet to completely solve. We might look to how we solved similar problems in the past and apply some of that thinking to the new context, or we may have to look for new innovative approaches.


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