IoT Explained
24 October 2024
Reading Time: 5 mins
IoT Explained
24 October 2024
Reading Time: 5 mins
Eseye
IoT Hardware and Connectivity Specialists
LinkedInOne of the key drivers behind the growth in IoT is the value that can be unlocked through data analytics. Large numbers of devices equipped with sensors capable of reporting on an almost unlimited number of data points creates a huge opportunity for enterprises to create process optimizations or new revenue streams.
But aggregating, managing, storing and analyzing the massive amounts of data generated by IoT devices presents its own challenges, and the cloud plays a critical role in the storage and computation of IoT data.
Connectivity between IoT sensors and the cloud is also essential for the benefits to be realized, as the data generated by IoT devices needs to get to the right place at the right time.
Due to their small form factor, IoT devices have either very limited local storage capability or none at all. Furthermore, many devices, such as building temperature management actuators or vending machines, require processing power to make decisions and complete actions, or forward information on to a central repository where it is pooled with other data.
A centralized cloud instance from one of the hyperscalers like AWS, Microsoft Azure, or Google Cloud provides access to significant compute and storage and can help connect information from multiple data sources. Similar capabilities are provided by more specialist or geographically niche clouds like IBM Cloud, Oracle Cloud, or Huawei Cloud.
Cloud computing is typically delivered in three service models, and adoption depends on your requirements:
In terms of management of your IoT estate, the cloud is also important in delivering the ability to manage devices and applications from an integrated singular interface. This would likely be provided as a SaaS-type service from your IoT service provider.
As a centralized infrastructure asset with highly flexible storage and compute power, as well as onward connectivity to other clouds and data centers, public cloud environments introduce several key benefits.
Data storage and aggregation
Cloud stores, whether buckets, blobs, warehouses or data lakes, are capable of collecting IoT data generated by thousands or millions of IoT sensors. The data can be stored and processed in a central location with easy access to associated compute services. It could also be integrated with data in other clouds through inter-cloud connectivity, enabling applications and analytics tools to benefit from multiple data sources.
Scalability
The cloud is highly scalable and extends these benefits to IoT deployments. Cloud infrastructure can easily handle data from thousands of devices and more capacity can be added as and when needed. The global availability of the hyperscalers also makes it easy to deploy into new geographic regions.
Flexibility
The cloud also gives IoT deployments a great deal of flexibility. Cloud storage and compute can be flexed up and down with demand, and cloud connectivity can typically be flexed in line, adding or reducing capacity to move data from place-to-place faster or flexing bandwidth in line with real-time or seasonal demand.
Reduced maintenance
The cloud model typically swaps CAPEX for OPEX, removing ownership and associated costs of the hardware which instead is maintained by the cloud service provider.
Cost
Although the ‘cloud is always cheaper’ mantra has been frequently debunked in recent years, it can certainly help make the costs more manageable at the start of an initiative and as you grow. The elastic nature of infrastructure and resources mean you only pay for what you use and you can add more assets on demand.
The cost traps to look out for are around egress fees. While it generally costs nothing to put data into the cloud, it can be expensive to get data out.
Given the complexity or specific use case of some IoT deployments, a centralized cloud might not always be the answer. Options such as edge computing, or fog computing, can bring processing power physically closer to where the data is generated.
‘Cloudless’ platforms, such as Microsoft Azure IoT Edge, enable organizations to run workloads on edge or fog compute devices closer to the source and might be useful for remote facilities or locations where cellular network connectivity is limited or unavailable.
Edge networking
This moves hardware to the network edge and may be able to perform some simple computation and storage, but is more likely to act as a gateway that aggregates data from multiple IoT devices.
Fog nodes
As the name suggests, fog nodes are less dense than a cloud but reside closer to the network edge and are typically single pieces or clusters of hardware outside of a cloud or data center. Fog nodes are able to provide the required compute or storage at a physically closer location to the IoT endpoints.
Smart cities and buildings
Critical components of an IoT smart cities or smart buildings platform include IoT sensors to collect data and transmit it to a centralized cloud management platform, where compute services perform the data manipulation and insight extraction.
In a city or campus environment, edge compute or fog compute devices can be used to manipulate the data at the network edge, close to where the sensors are deployed. Or data from multiple field sensors can be combined in the cloud to provide a broader picture of the overall IoT system and deliver actionable insights.
Healthcare
The healthcare and medical devices sector is dominating the IoT adoption race, with larger deployments of devices than any other industry.
Telehealth equipment helps people to manage long-term health conditions from the comfort of their own home with remote telehealth devices worn on the patient’s body, collecting data about their vital signs and transmitting it to the cloud. This enables a doctor or physician to regularly monitor the patient’s health using data from the device.
Manufacturing and Industry 4.0
Industrial IoT (IIoT) or Industry 4.0 account for the application of IoT technology to enable Smart Manufacturing as part of a global trend which also encompasses big data, the cloud, automation and robotics, Human-Machine Interaction (HMI), 3D printing, and the adoption of cyber-physical systems, all collaborating to bring manufacturing into a mixed reality of the physical, augmented, and virtual.
IoT communication technologies can be integrated into a wide range of devices throughout an industrial automation system for different use cases, from the supervisor level all the way to the control and field levels aggregated and controlled in the cloud.
Grow and rapidly scale your IoT deployments to unlock the full potential of IoT deployments. One of Eseye’s strengths is its ability to provide scalable IoT connectivity across different regions and industries, enabling businesses to expand their IoT deployments without worrying about infrastructure limitations.
Secure Cloud Connect enables your IoT devices to seamlessly and securely communicate, whatever your cloud, including hyperscalers such as AWS IoT, Azure IoT and Google Cloud.
Eseye specializes in providing reliable, global IoT connectivity and cloud computing is a fundamental enabler of IoT, offering the necessary infrastructure for managing and analyzing the data from connected devices. Eseye’s Infinity IoT Platform provides a single cloud-based way of managing your entire IoT estate. From SIM provisioning and activation to configurable reports and alerts, and a single point of billing.
Eseye
IoT Hardware and Connectivity Specialists
LinkedInEseye brings decades of end-to-end expertise to integrate and optimise IoT connectivity delivering near 100% uptime. From idea to implementation and beyond, we deliver lasting value from IoT. Nobody does IoT better.
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