Cloud Platforms

 

 

  IoT Cloud Platforms.

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IoT cloud platforms bring together capabilities of IoT devices and cloud computing delivered as a end-to-end service. They are also referred by other terms such as Cloud Service IoT Platform. In this age, where billions of devices are connected to the Internet, we see increasing potential of tapping big data acquired from these devices and processing them efficiently through various applications.


IoT devices are devices with multiple sensors connected to the cloud, typically via gateways. There are several IoT Cloud Platforms in the market today provided by different service providers that host wide ranging applications. These can also be extended to services that use advanced machine learning algorithms for predictive analysis, especially in disaster prevention and recovering planning using data from the edge devices.

 

  •      What are the key features of an IoT cloud platform?



 


An IoT cloud platform may be built on top of generic clouds such as those from Microsoft, Amazon, Google or IBM. Network operators such as AT&T, Vodafone and Verizon may offer their own IoT platforms with stronger focus on network connectivity. Platforms could be vertically integrated for specific industries such as oil and gas, logistics and transportation, etc. Device manufacturers such as Samsung (ARTIK Cloud) are also offering their own IoT cloud platforms.

 

In most cases, typical features include connectivity and network management, device management, data acquisition, processing analysis and visualization, application enablement, integration and storage.

 

Cloud for IoT can be employed in three ways: Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) or Software-as-a-Service (SaaS). Examples of PaaS include GE's Predix, Honeywell's Sentience, Siemens's MindSphere, Cumulocity, Bosch IoT, and Carriots. Developers can deploy, configure and control their apps on PaaS. Prefix is built on top of Microsoft Azure (PaaS). Likewise, MindSphere is built on top of SAP Cloud (PaaS). Siemens's Industrial Machinery Catalyst on the Cloud is an example of SaaS which is a ready-to-use app within minimal maintenance.


  •    How is an IoT cloud platform different from 

     Traditional cloud infrastructure?

The traditional cloud infrastructure focuses on a model of cloud computing where a shared pool of hardware and software resources are made available for on-demand access in such a way that they can be easily and rapidly provisioned and released with minimal effort. IoT Cloud Platform extends this capability to resources that are more user-centric, which increases the count and scale of data and devices. The cloud platform services can not only process big data from a wider set of IoT devices, but also provides a smart way to provision and manage each of them in an efficient manner. This also includes fine-grained control, configuration and management of IoT devices.

 

  • · Some IoT cloud platforms out there in the industry today





With the advent of IoT with billions of devices getting connected to the internet which not only does compute, storage and run applications, there is also a needed to handle large amounts of data coming into the system via the various interfaces such as sensors and user inputs.

 

Here are some IoT cloud platforms:

 

  •        Amazon Web Services IoT
  •        IBM Watson IoT Platform
  •   m  Microsoft Azure IoT Hub
  •       Google Cloud IoT
  •       Oracle Integrated Cloud for IoT
  •       SAP Cloud Platform for the Internet of Things
  •       Cisco Jasper Control Center
  •       PTC ThingWorx Industrial IoT Platform
  •       Salesforce IoT
  •       Xively
  •       Carriots


    Benefits of Cloud Platform in IoT


One of the greatest advantages of placing your IoT system in a cloud is that it is very easily scalable. In case of complex on-premise network infrastructures, scaling up requires purchasing more hardware, investing more time and undertaking increased configuration efforts to make it run properly. In a cloud-based Internet of Things system, on the other hand, adding new resources usually boils down to leasing another virtual server or more cloud space which both usually have the extra advantage of being quickly implemented. Moreover, IoT cloud platform services offer more flexibility in case you want to limit your storage requirements or scale down the number of IoT-enabled devices.


With your data stored and processed in a cloud server, it can be accessed from almost anywhere in the world, which also means that it won’t be bound by any infrastructural or networking constraints. Mobility is especially important when it comes to IoT projects involving real-time monitoring and management of connected devices. While data stored in on-site servers can be only acted upon within the company’s premises, an advanced Internet of Things cloud platform will give you the tools to provision, manage, and update your devices and sensors and process the acquired data remotely and in real-time



     Security issues, which have been a major concern for the IoT world ever since its inception, can be a tough one here. In the cloud platform vs. on-premise IoT infrastructure clash, it’s all about responsibility. In case of on-site servers, it lies in the hands of the company and it only depends on the security practices within the organisation if the data is kept safe. Therefore, it is quite understandable that some organisations may feel uncomfortable about giving up control over their sensitive data and passing it to an external party. Yet, there is common agreement among both the service providers and clients that storing and processing your Internet of Things data in the cloud is more secure than keeping it on prem. Thanks to the possibility of regular software and firmware updates as well as 24/7 monitoring offered by some platform providers, major security breaches can be avoided




 

·       What are some challenges of adopting IoT cloud platforms?

Security and privacy are the main concerns delaying the adoption of IoT Cloud Platforms. Cloud providers typically will not own the data and are only authorized to do the analytics and control of systems as permitted by the owner of the data. Any breach of data access either during transit or from storage is a concern from privacy and security perspective. Also, since the value of IoT data is immense, proper legal agreements and mechanisms must be in place to ensure the data or outcome of data analysis is only used for the intended purpose by the authorised personnel.

 

Existing IoT cloud platforms may not always conform to standards, thereby causing interoperability issues. They may also not support heterogeneous modules or communication technologies. When there's too much data, context awareness can help, including decisions of what needs to be done at the edge. Vertical silos continue to exist and this prevents horizontal flow of information. Middleware can solve this problem. Many system continue to use IPv4 and this could be a problem as devices run out of unique IP addresses.

 

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