WHY IS PLATFORMSIOT NECESSARY
The number of connected devices is set to grow from 13.2 billion in 2022 to 48.1 billion in 2030, an annual growth rate of 17.5%. This means the rate of new product introductions is speeding up. None of the 48.1 billion devices will connect to the cloud on their own. As IoT becomes an increasingly important part of business and commercial operations, the range of application areas for IoT has increased enormously. As a result, the need for IoT connectivity to operate effectively and securely anywhere on the planet is also increasing – on land, sea and air. This is not going to slow down any time soon.
IoT creation, deployment and management process is incredibly complex and requires specialized skills in at least 5 different engineering disciplines. Absolute majority of potential customers do not employ or plan to employ or develop engineers with specialized skills. Most consumers want their data and they want it near real time and with time to market strategy ASAP.
The IoT devices, before they can connect, must be onboarded to cloud services that accept connections from IoT devices. This requires setting up complex procedures like creating device policy, device groups , creating topics and issuing certificates, creating lambdas for moving data from cloud topics to live databases. The process requires a special type of engineers, known as cloud engineers.
The certificate must be loaded into the device in order to connect to the cloud topic and publish data. Data must be published using MQTT or other protocols in order to be usable. The device must establish a connection via 2G, 3G, LTE, CAT-M, NB-IoT , WiFi, LoRaWAN, BLE or other protocols. The data flow requires permission from carriers over cell networks or connectivity credentials for local networks. These and other device activities require a special type of engineers known as firmware engineers.
When data is published, it is usually published as raw data. In order for data to become a business data, it needs to be post processed, organized in canonical form and served to business. The data should be either integrated into existing business processes or databases. The product commonly known as middle tier application requires engineers with Object Oriented Programing skills. Usually written in java or .NET the middle tier also creates an API for integration and provides data flow to databases used by businesses. Usually built on microservices architecture, the middle tier is the connecting link between hardware and business.
When IoT data is streamed to the cloud , it comes in a raw form. Specialized NoSQL databases exist to accept the data. They often need specialized engineers with understanding of the retention policies, time stamps and event handlers like Kafka or message queues like RabbitMQ. On top of everything , the majority of businesses use structured RDBS or NoSQL databases for business processes. Transformation is an incredibly complex process , involving programming and configuring databases, event handlers and message queues. The engineering discipline is known as database administrators, but in the IoT world it is a very different skill set on top of traditional database administration.
Frictionless data collection is a process where data is collected in the cloud by simply turning on the device. Although it is a very simple concept to understand, it is increasingly complex to achieve. However, frictionless data collection is the only way of getting data from device to AI models, machine learning algorithms and data lakes.
Faceless data collection is a process where data is collected without identifying the source etc. It is the opposite of defacing data, because it starts faceless. In the traditional data collection model, a range of redundant, often personal information is collected as part of the dataset. Faceless data collection assumes no identification information, just indexing. Obviously it can be faced anytime, for business use, but collection and distribution is kept sterilized. This process has incredible advantages because it solves data security in principle.
Market need for PlatformsIoT : We created scalable and reusable platform features that refactor most commonly used processes into platform for fastest and most reliable path from device to business. Let’s consider a business analogy: everyone loves word processors like Microsoft World or Google Docs. The word processor will not type for you, still requires a user to type. However formatting, line returns, spell checkers and other features make it a better choice over simple text editors. And just like word processor formats, correct and print your thoughts in a manner that you can use, the PlatformsIoT gives you your data in a formatted, canonical form