The phenomenal growth of IoT is undeniable — in 2021, there are more than 10 billion active IoT devices and that number is estimated to climb to 25.4 billion by 2030. At the same time, cloud computing is experiencing exponential growth, with 83 percent of enterprise workloads already based in the cloud and 94 percent of enterprises using a cloud service.
IoT and cloud computing are growing at similar rates because they work together in a symbiotic relationship. IoT devices generate data, which needs to be aggregated and processed either in a local server or remotely. In many IoT applications, remote data hosting and analytics is a more affordable and practical solution. The total amount of data IoT devices will generate is expected to reach 73.1 ZB (zettabytes) by 2025, demanding tremendous computing power — and cloud computing can provide that power.
Recommended reading: The Ultimate Guide to the Internet of Things
What’s the difference between IoT and cloud computing?
The Internet of Things (IoT) consists of connected sensors or other devices that transmit data through a network of some kind, typically cellular or internet-based.
Cloud computing runs software and stores data on remote servers, allowing for far greater processing power than most local drives can provide.
Is IoT built on cloud computing?
Short answer: Yes. Utilizing the cloud allows for processing outside of the device itself, which is often impossible or expensive to implement on small devices or edge processors.
Recommended reading: IoT Architecture Explained: What is It and How Does It Work?
Let’s take a closer look at how IoT devices and cloud computing work together.
IoT devices talk to one another over networks to accomplish tasks. Often called smart devices, they might monitor industrial processes, allow users to control home functions like lighting and HVAC systems remotely from a smartphone app, or track soil moisture levels in agriculture fields. The cloud refers to remote storage and processing of massive amounts of information distributed among servers all over the world. A group of IoT devices is often connected to remote storage and processing units in the cloud. As the devices collect data, they transfer it to a cloud server (either directly or via a local IoT gateway), where it can then be accessed and analyzed through an internet portal, typically on a mobile application or website. For example, IIoT sensors gather readings to gauge the health and performance of machinery on the factory floor. Routing the data through a local gateway, they transfer that information to a cloud server where it’s aggregated and analyzed. C-suite executives and offsite managers can then access data dashboards and reports about the machines’ performance, helping them track overall productivity at the smart factory.
Recommended reading: What’s the relationship between IoT and big data?
What role does cloud computing play in the Internet of Things (IoT)?
As already mentioned, cloud computing plays a key role in many applications of IoT. Let’s look closely at a few ways the cloud benefits and provides infrastructure for IoT deployments:
Inexpensive data management
With the growth of big data, IoT devices often generate so much information that it would be difficult to store and manage all of it at the edge. Because of its endless capacity, cloud computing provides a convenient and affordable solution for data management. Instead of maintaining expensive on-premise servers, companies can transfer data from their devices to a remote cloud, typically paying the cloud provider a periodic as-a-service fee rather than investing in their own hardware (and having to hire IT personnel to maintain it). This reduces the total cost of ownership for operating an IoT deployment, as cloud providers manage all hardware infrastructure, maintenance issues, and security updates.
Because IoT devices generate data in real-time — and many never stop creating more — data storage is a potential hurdle for many applications. Cloud computing solves this dilemma with its virtually unlimited storage capacity, allowing companies to maintain uninterrupted records of IoT data over time and giving them greater insights and reports on productivity changes and growth.
Enhanced, remote processing capabilities
Dealing with mind-blowing amounts of data is no job for normal PCs or even powerful edge computing hardware. Because it depends on virtual machines that imitate hardware components, cloud computing infrastructure can provide the tremendous processing power needed to handle data pouring in from IoT devices. There are also practical advantages to processing data remotely — it eliminates the need to purchase and take up physical space with high-level hardware, or provide electrical power for that equipment.
With many developers involved in creating and managing an IoT deployment, remote cloud processing allows those working on new features to interface more easily with the devices and engage in programming and app development. For example, if you are using cloud processing power to monitor the level of overheating in a manufacturing machine, a developer could use that data to build a predictive algorithm to better regulate the devices’ operation — and then remotely configure the devices to implement the new algorithm.
Security and privacy
Initially, many companies were hesitant about adopting cloud because they felt their data was safer on premise than it would be if transmitted and stored on remote servers over which they have no control. While that’s a legitimate concern, many of today’s cloud providers make security a top priority, and there are many reasons why enterprises now view cloud computing as more secure than on-premise storage and processing. Legacy hardware accumulates security vulnerabilities as it ages, becoming less compatible with newer systems and more difficult to update with the latest security patches. On the other hand, cloud infrastructure has built-in security capabilities, and most providers constantly survey current threats and update security patches automatically. When security is handled by your provider, it frees you up to focus on IoT devices and applications rather than pouring time and costs into cybersecurity.
Depending on the industry or sector, companies must ensure that their data collection and management complies with applicable regulatory mandates and government restrictions. Maintaining adequate compliance and generating reports to prove it can be burdensome to companies with on-premise servers, and this is another area cloud computing can simplify. Cloud operators are required to comply with privacy laws and regulatory standards, such as PCI, SOC, FedRamp, and ISO, removing the burden from their customers and providing assurance that data will be handled securely.
Because cloud processing uses portions of already existing servers, a business can scale immediately by simply paying for more cloud storage and processing power. If the need diminishes later, they can simply scale back and not pay for as much. It’s like renting an (infinitely expandable) apartment with a monthly lease instead of building a house — if you suddenly need to move, no big deal.
Outsourcing data storage and processing to the cloud means your company does not need to invest in hardware beyond the IoT devices themselves and perhaps a gateway device. Rather than having to purchase a central processing hub in the form of a local server, the cloud allows all of that computing to be spread among other servers that you are only renting for the needed time. This is particularly beneficial for devices that have intermittent high processing demands. Why buy top-of-the-line hardware if it will only be in use 5 percent of the time? Cloud computing in conjunction with IoT deployments also allows you to save on IT personnel. Rather than employing a team of IT experts — not to mention cybersecurity professionals — to maintain local servers, choosing a cloud solution means you can leave all of that management to your provider.
Cloud Computing and IoT: What’s the Future?
As IoT and cloud computing continue to expand, there’s also a lot of buzz around edge computing — keeping some data processing power at the network edge rather than outsourcing everything to the cloud. Edge computing shows tremendous promise for real-time data analytics and can help limit the need for cloud storage by pre-filtering data and transferring only some of it to remote servers. However, moving all data processing and storage back to the edge is impractical for most companies, so in the future, edge computing is likely to function alongside IoT devices and cloud computing, helping to provide an even better framework for the ever-increasing data streams from massive IoT applications.
Recommended reading: Edge computing in IoT: 5 reasons it’s important
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