The Internet of Things (IoT) is expected to change dramatically in 2017, with technology, improved consumer experiences, and digital marketing. Companies need to implement changes to remain competitive in their respective industries. Every aspect of a company’s IoT system needs to be integrated and working together.
The market for Internet of Things (IoT) platforms is rapidly growing and changing. We need to be very clear on the expectations from IoT platforms before we select one.
This article intends to help you with understanding of platform requirements.
The Internet of Things (IoT) term was first introduced by Kevin Ashton in the year 1999. IoT has become a promising technology with a lot of potential for easing the effort and helping humanity and businesses.
Currently there are two types of vendors in market providing IoT platforms, one hardware and another software platforms, majority of vendors are focused on the hardware. There are few vendors in market who offer IoT software platforms, few prominent provider are as follows.
|IoT Provider||IoT Platform|
Designing and developing IoT solutions is no simple task, there are some patterns suggested for IoT solution designs, please refer article here for the same. It is way complex task and it involves hardware, devices, deployment, telemetry, efficient storage, analytics, machine learning and BI, bundled in as one offering.
IoT is helpful only if all these aspects are taken into consideration during designing and developing solution.
What to expect from IoT Platforms
Now a days almost all the things in the world are getting connected, IOT help in connecting the physical devices, hardware and machines to the digital world in meaningful and productive ways. It also helps in industrial automation data. IoT platforms ingest data from all the devices which is called telemetry, helps to integrate IT systems and make data visible to key stakeholders so they can visualize, plan, predict and take decisions.
If you want to implement IoT solution then selecting right fit of platform can be a challenging task. You need to be aware of what each vendor is offering.
The actual importance of IoT for businesses lies in the data, which is ingested by devices, and these devices can potentially emit millions of data points every day, but the challenge is to make use of this data for the benefit of business, in many cased this data remains unused. collating and making sense of this data is a huge task.
Hence it is very important to investigate the IoT platform landscape, each of the related features are supported and implemented to different extent by different providers.
Following features are crucial for an IoT platform.
|1. Support for REST APIs and Integration|
|2. Management of Devices|
|4. Support for Lightweight Communication Protocols|
|5. Support for Analytics of Data|
Let’s see one by one how important these features are for IoT platforms.
Support for REST APIs and Integration
IoT platforms should provide ability to create and market APIs. Integration is important feature expected from an IoT platform. APIs are things/devices facing, they are also very important for IoT platforms as they provide ability to connect applications to devices. For example, a connected car can have an app that can unlock the doors.
Developers on the device side and data side are different, and they would have different rights, different APIs, and different security requirements. APIs should provide access to the operations on devices as well as in data.
Management of Devices
There are four fundamental device management requirements exist for any Internet of Things (IoT) device deployment.
1. Provisioning and authentication.
2. Configuration and Control
3. Monitoring and Diagnostics
4. Software updates and Maintenance
Management of Devices is one of the most important features expected from any IoT software platform. The IoT platform should maintain a list of devices connected to it and track their operation status; it should be able to handle configuration, updates and error handling.
Modern IoT devices architecture should have bi-directional communication and flexible to allow for all network components to be connected and observed. In case of damage, or a security breach, the platform can remove the device. It should be possible to get the status and statistics of each device.
Security is an important aspect of an IoT platform like any other standard software application. Millions of devices gets connected with an IoT platform, hence we need to anticipate a potential vulnerabilities. Communication between the IoT devices and the IoT software platform need to be encrypted with a strong encryption mechanism to avoid potential attacks.
Most of the traffic in IoT communication comes from computing devices and embedded sensor systems used in industrial machine-to-machine (M2M) communication, smart energy grids, home and building automation, vehicle to vehicle communication and wearable computing devices.
To improve security, an IoT devices that needs to be directly accessible over the Internet, should be segmented into its own network and have network access restricted. The network segment should then be monitored to identify potential anomalous traffic, and action should be taken if there is a problem. (Most of the modern IoT devices have support for having public and private IP)
Support for Lightweight Communication Protocol
Data collection protocol, another important aspect which needs attention is the types of protocols used for data communication between the components of an IoT software platform. An IoT platform may need to be scaled to millions or even billions of devices (nodes). Lightweight communication protocols should be used to enable low energy use as well as low network bandwidth.
There are couple of emerging light weight messaging protocols. The first, MQTT, is very old by today’s standards from way back in 1999. And the second, CoAP, is relatively new but gaining traction.
Support for Data Analytics
The data collected from the sensors connected to an IoT platform needs to be analyzed in an intelligent manner in order to obtain meaningful insights.
There are four main types of analytics which can be conducted on IoT data:
1. Real-time analytics
2. Batch analytics
3. Predictive analytics
4. Interactive analytics
Real-time analytics conduct online (on-the-fly) analysis of the streaming data. Example operations include window based aggregations, filtering, transformation and so on.
Batch analytics runs operations on an accumulated set of data. Thus, batch operations run at scheduled time periods and may last for several hours or days.
Predictive analytics is focused on making predictions based on various statistical and machine learning techniques.
Interactive analytics runs multiple exploratory analyses on both streaming and batch data.
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