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Guides Strategy How to select the right IoT platform for your business

How to select the right IoT platform for your business

Published on 11/10/2016 | Strategy

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Anastasiya Zakharchuk

Business Development Manager at Altabel Group. She handles responsibilities including: - end-to-end customer management; - business development; - planning and overseeing new marketing initiatives; - creating, negotiating and closing commercial agreements; - marketing and promotion activities.

IoT GUIDE

Overview

As the Internet of Things begins to revolutionize businesses, economies and our society, IoT platforms are coming up being the core basis in the overall IoT infrastructure. IoT platforms, in simple words, are just about connecting the sensors to data networks and integrating with back-end applications to provide insight into huge volumes of data.

However developing for the Internet of Things is a complicated undertaking, and almost nobody chooses to do it from scratch. IoT data platforms provide a starting point by integrating many of the tools needed to operate a deployment from device control to data prediction and grasp into one service. Ready-built IoT platforms can meet the needs of any company and smoothly accommodate constant growth and change. In the light of the possibilities offered by IoT, many high tech companies started taking advantage of it. For the time being there are more than 300 hundred various IoT platforms on the market and the number is continuing to grow. So, let’s see what features of IoT platforms take into consideration while choosing one for your business.

Before selecting an appropriate solution which may be suitable for your organization, you must determine:

1. Three different types of IoT platforms

Here they are listed from most complex to least complex:

Application enablement and development (AEP/ADP): This encompasses platforms that offer modules, widget-based frameworks or templates for producing (with minimal or no coding) actual end-user applications. These platforms are capable of turning data into either intelligence or action very quickly. The vivid examples of such platforms are Oracle, ThingWorx and etc.

Network/Data, and subscriber management (NM): In the wireless carrier and mobile virtual network operator (MVNO) space, this kind of platforms try to streamline connecting cellular M2M data, so you don’t have to build much of the data infrastructure behind it. For instance Cisco and Aeris do network management as well as device management, while Jasper and Wyless do more sheer network management.

Device management (DM): These platforms are more about monitoring device statuses, troubleshooting issues, configuring embedded device settings and administrating the provisioning and health of the endpoints. Usually in the IoT space this fairly elementary software is provided by hardware vendors. Like both Digi and Intel provide pure device cloud management.

While these platforms can be found as distinct standalone products, it is becoming increasingly common to find vendors that combine two or all three types in a single offering.

2. Implementation, integration support and device management

Device management is one of the most significant features expected from any IoT software platform. The IoT platform should maintain a number of devices connected to it and track their proper operation status; it should be able to handle configuration, firmware (or any other software) updates and provide device level error reporting and error handling. Ultimately, users of the devices should be able to get individual device level statistics.

To make implementation smooth, the provider should possess convincing manuals, blogs and feasibly lively developer-community around the IoT platform.

Support for integration is another vital feature expected from an IoT software platform. The API should provide the access to the important operations and data that needs to be disclosed from the IoT platform. It’s typical to use REST APIs to achieve this aim.

3. Comprehensive Information Security

There are four main technological building blocks of IoT: hardware, communication, software backend and applications. It’s essential that for all these blocks security is a must-have element. To prevent the vulnerabilities on all levels, the IoT infrastructure has to be holistically designed. On the whole, the network connection between the IoT devices and the IoT software platform would need to be encrypted and protected with a strong encryption mechanism to avoid potential attacks. By means of separation of IoT traffic into private networks, strong information security at the cloud application level, requiring regular password updates and supporting updateable firmware by way of authentication, signed software updates and so on can be pursued to enhance the level of security present in an IoT software platform. Nonetheless while security ought to be scalable, it is unfortunately usually a trade-off with convenience, quick workflows and project cost.

4. Flexible Database

There are four major “V” for databases in IoT space:

- Volume (the database should be able to store massive amount of generated data)

- Variety (the database should be able to handle different kind of data produced by various devices and sensors)

- Velocity (the database should be able to make instant decisions while analyzing streaming data)

- Veracity ( the database should be able to deal with ambiguous data in some cases produced by sensors)

Therefore an IoT platform usually comes with a cloud-based database solution, which is distributed across various sensor nodes.

5. Data analytics

A lot of IoT cases go beyond just action management and require complicated analytics in order to get the most out of the IoT data-stream. There are four types of analytics which can be conducted on IoT data: 

- Real-time analytics (on the fly analysis of data),

- Batch analytics (runs operations on an accumulated set of data),

- Predictive analytics (makes predictions based on different statistical and machine learning technologies)

- Interactive analytics (runs numerous exploratory analysis on either streaming or batch data)

While choosing the right IoT platform, it’s better to keep in mind that the analytics engine should comprise all dynamic calculations of sensor data, starting from basic data clustering to complex machine learning.

6. Pricing and the budget

 

The IoT platform market features a diversity of pricing methodologies underlying various business strategies. And sometimes providers’ costs aren’t always transparent. Thus it’s very important to check out all the nuances of your provider’s pricing pattern, so you are not plainly bought into introductory teaser rates or into the prices for the base model.

Further you should bear in mind that you licensing cost for the chosen platform is just the beginning. The major expense can turn out to be the integration itself, as well as hiring consultants (if you are not able to do it on your own) to support the system.

Therefore, it’s extremely vital to brainstorm what your entire IoT system will look like at scale and choose which features are most critical to you chiefly — and only afterwards decide what sort of platform you need.

A lot of companies do this backward. They get the IoT platform and believe they’re getting the complete necessary solution—then realize the mistake half a year into development. Thus it’s critical to be aware of this before you get started.

Also it should be mentioned that some companies don’t use IoT platforms—they’re developing their own platforms in-house. Yet, depending on how you want to go to market, it may be clever to research pre-built options. Depending on your situation, you may save a lot of time and money by partnering with one of these platforms. 

Have you ever faced the difficulties of choosing the IoT platform for your business? If yes, can you please let me know what kind of difficulties? And what do you think is it better to use a ready-built IoT platform or develop your own from the scratch? Looking forward to getting your ideas and comments.

This article was originally posted on LinkedIn.

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