Combining technologies to maximise the potential of the Internet of Things

We are increasingly using the Internet of Things in our daily lives – from controlling the temperature of our homes remotely, to checking our smartphone for real-time travel updates and asking Alexa (or Siri) to play a particular song.

As the IoT expands, the amount of data being generated and shared balloons too, making the issues of data storage and data security ever more challenging.

Other computing fields, like blockchain and edge computing are advancing at pace and helping to secure the future of the IoT ecosystem, taking it beyond smart homes and smart cities to the evolving industrial internet of things. Read on to find out how.

Blocking hackers with blockchain

A perennial problem for the IoT is security, which has hampered IoT applications. The IoT is made up of a myriad of devices, sharing huge amounts of data, much of which is personal and sometimes sensitive. Until recently IoT security was reliant on all connected devices being password protected to prevent rogue access and hackers, but now blockchain is coming to the rescue.   

Blockchain is highly secure and its uses go way beyond bitcoin. Cryptocurrencies such as bitcoin and Ethereum use blockchain technology, where data is stored in decentralised blocks. Each transaction is encrypted and linked to the previous transaction or data block in a chain, making it very difficult to hack. The integration of blockchain into IoT data storage systems can protect IoT devices from cyberattacks such as Distributed Denial of Service attacks (DDoS).

When data integrity is paramount, such as in healthcare or supply chain management, using a blockchain network can ensure the data shared via the IoT is safe from external tampering.

Scaling up by breaking up

Although the IoT shares data from remotely connected devices, traditionally, IoT systems have relied on centralised servers for data processing. This can stifle growth as there are limits to the amount of data that can be handled by a central store. With blockchain, data storage is decentralised and data stored across multiple nodes, removing the potential for a single point of failure and allowing almost limitless scalability. This is where edge computing comes into play too.

Computing at the edge

Rather than transferring data to a centralised cloud computing hub for processing and analysis, edge computing means data is stored and processed near to where it is generated at the ‘edges’ of the network on edge devices. This is becoming known as fog computing and it not only helps reduce the risk of big data breaches but can address issues of internet bandwidth and latency. In addition, data privacy is secured by avoiding the transfer of data from remote computing systems across insecure connections.

Autonomous transactions

The IoT is all about allowing devices to communicate directly without the need for central coordination or authority. By using blockchain for smart contracts and secure transactions, devices can act more autonomously. Use cases include smart fridges that can sense when particular groceries are running low and automatically place an order to replenish supplies.

The integration of blockchain and edge computing together create a scalable and flexible infrastructure that is allowing the IoT to grow in a more secure and decentralised framework.  This is allowing the IoT to become ever more useful and exploited in new ways.

Designing robust and secure integrated frameworks

Increasingly, advanced technologies like IoT, machine learning and robotics are being integrated into systems for manufacturing and supply chain management, creating systems that are forming what has become known as Industry 4.0. But as the number of devices connected increases, unauthorised access to data becomes an ever bigger issue. Cyber attacks can disrupt production processes and supply chains. In addition, more benign issues with interoperability can also cause disruption.

Decentralised architectures using edge devices and fog computing, coupled with the sophisticated cryptography of blockchain enabled tech, are transformational. Integrating efficient and light weight consensus algorithms suitable for edge devices and IoT devices, that often have more limited computational capacity, supports better integration and allows heterogeneous devices to work together.

Industry standards

There is now wide recognition that to ensure such systems are secure for use in global settings, industry regulation and standards are required. The IEEE is an organisation that brings experts together at international conferences and encourages collaborations and knowledge sharing to develop consensus mechanisms and industry standards across a range of technologies. 

Other organisations such as publishers Springer and the Association of Computing Machinery (ACM) are encouraging the tech industry to work together to drive forward adaptive technologies that improve functionality and interoperability of products and services on a globally level playing field for innovation that can contribute to a more sustainable future.

Enhanced supply chain management

Increasingly the IoT is being exploited by businesses in resource management and creating the industrial internet of things (Industrial IOT). By combining the security benefits of blockchain, the scalability afforded by mobile edge computing (MEC) and the flexibility of the internet of things, the possibilities seem endless. These new computing paradigms are facilitating more efficient, secure and sustainable supply chain management system in several ways:

Reducing fraud

Blockchain technology ensures transactions are secure and remain traceable, despite distributed computing, allowing the authenticity of products to be verified and traced.

Improving decision-making in real-time

The IoT allows vast amounts of data to be collected at various points in the supply chain. Edge computing environments mean the data can be analysed close to where it is created, rather than offloading it to central servers and thereby speeding processes and allowing the metrics to inform real-time decision-making, such as pricing, to improve business efficiency.

Securing private data

Both permissioned blockchain and edge computing are helping to keep IoT data more secure. Together with cryptography and appropriate access controls these privacy-preserving mechanisms are expanding the ways the IoT can be used.

Making the most of bandwidth

Some locations experience limited bandwidth. By storing and processing more data locally using edge computing resources, this limitation can be overcome and help to ensure continuous operations throughout IoT networks.

Reducing operational costs

For businesses looking to reduce operational costs, exploiting the IoT in conjunction with blockchain based technology and/or edge computing to reduce the need for centralised data processing and data transmission can make a big difference.

Enhancing efficiency and reducing waste

By combining IoT sensors that monitor the condition of goods in transit with edge computing that can trigger action if issues are detected, supply chains can be optimised and waste reduced.  

Real-time visibility coupled with predictive analytics can also prevent disruption and improve the resilience of supply chains.

The sustainability of the supply chain can be further enhanced by using sensors and real-time monitoring to ensure allocation of goods and transport routes are efficient, reducing emissions and ensuring speedy delivery of products.

Taking the IoT to the edge

If you are interested in developing your knowledge and skills to help contribute to the optimization of the IoT in sustainable ways to enhance our lives, an online MSc computer science from Sheffield Hallam could be for you.

The online masters course ensures you’re ready to excel in the fast-paced tech landscape, providing you with the in-demand skills to program across diverse platforms, languages and applications, and arms you with the latest expertise in data management, DevOps engineering, applied machine learning and artificial intelligence and information security.