Integrating any digital technology into well-established processes is not easy, let alone something as complex as Internet of Things. Often, businesses confront the usual IoT challenges like lack of skills and underestimated cost and effort. However, this is far not the complete list.
In this blog, we will highlight the less obvious but very influential challenges in implementing IoT and provide some advice on how to manage them.
- Choosing the right IoT platform solutions
The main motive of an IoT platform is to bring physical objects online. Be it an end-to-end IoT platform, a connectivity management platform, an IoT cloud platform, or a data platform – it must be able to support hundreds/thousands/millions of device connections simultaneously and allow you to easily configure your devices and systems for seamless machine-to-machine communication.
- Choosing the right Hardware
Choosing the right hardware to make things connected can be one of the major Internet of Things challenges. In most cases, an IoT project starts as a prototype with a limited feature set and coverage area. For this purpose, companies go for a simpler design, affordable boards, and other hardware, and a straightforward data model.
- Data Connectivity options
Connectivity is the core of the Internet of Things technology. For this reason, the choice of the right communication protocol and connectivity technology (Wi-Fi, Zigbee, Bluetooth, etc.) is crucial for the success of an IoT project.
- Data security
Among IoT challenges and issues, security is often underestimated and even overlooked. In fact, the security of IoT data cat be fully cut from the design in a prototype IoT project. However, considering data is the major component of an IoT system, treating data security as an afterthought is usually a big mistake. It opens the system for breaches, unauthorized control takeover, and data theft.
- Consistency
Another challenge of Internet of Things implementation is maintaining consistency of the data flow. As mentioned earlier, data is a fundamental part of an IoT system. Uninterrupted, consistent data flow is essential for its successful work. At the same time, IoT systems are typically multi-component and include a number of data points and modules for data processing, sorting, storing, etc. In this context, IoT developers need to make sure data is not only secured from outside attacks but is safe within the system and is reliably transferred between system blocks.
- Intelligence
At its core, the Internet of Things is about sensors embedded into devices of all kinds, which provide streams of data via the network to one or more repositories. The data can then be analyzed and acted upon so that it is beneficial to the business and its users.
IoT devices will evolve through intelligence applied to this data; intelligence in the form of machine learning and deep learning algorithms. This intelligence will look for patterns in the data so it can learn to adjust how it analyses that data.
These issues are major factors in influencing the decision-making process for enterprises and potential customers in order to ensure a successful IoT deployment.
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Resources:
https://www.digiteum.com/iot-challenges/
https://www.avnetworkshop.com/steps-for-successful-iot-deployment.html
https://www.singtel.com/business/articles/the-network-of-everything-top-5-considerations-for-your-iot-deployment
https://innovationatwork.ieee.org/6-things-to-consider-before-your-enterprise-iot-deployment/
