The six layers of an IoT solution

When people think of the IoT, they think of a Smart gadget or sensor, but if you want to assemble an IoT solution, six layers are considered under the IoT platform.

Each layer has requirements, considerations, and security consequences for achieving successful business solutions and ensuring data privacy and consent under IoT solutions.


The essential observations of your IoT system will emerge from a simplified data analysis. For a quick summary of the data from your device, leverage the built-in infographics. You can also easily interact with a dashboard builder like Grafana or use one of our predefined interactions to Azure IoT Hub and other specialized tools.


IoT gadgets

IoT gadgets are the “things” of IoT and can be as distinct as their applications – from tiny, low-powered devices with limited functionality under the IoT platform.

Such as temperature observation to extensive, high-powered tools that collect, exercise, and transmit multiple data types, like an autonomous vehicle under IoT solutions. Each IoT device has five components:

Sensors: A sensor is used to assemble data, while an indicator or actuator reacts to details.

Compute: This is the “intellectual” of the IoT gadget. All IoT devices require some form of onboard to compute, collect, store and transmit data under the IoT platform.

Connectivity: Every IoT device must transfer or receive data from the gadget to the data management area, which could be at the boundary, within your core database, or in the cloud under IoT solutions.

Power: This energy source will influence the device’s computer, sensors, or actuators, as well as data transport under the IoT platform.

Housing: The housing of IoT gadgets protects them from their operational domain. After all, many IoT devices are considered to prevent the requirement for humans to examine dangerous settings – like those with excessive heat, water, or vibration.

Edge computing:

IoT edges are network centers that often merge operational and information technology data under IoT solutions. With edge aggregating, computation and data testing are brought closer to the data source – where things and people generate or consume that data under the IoT platform.

Connectivity and data transfer

IoT association is the actual collection and transmission of data between gadgets and systems over a data connection under IoT solutions. When choosing to link an IoT device, the presence of the device to the web is a necessary examination, as are power, latency, and cost needs under the IoT platform.

Two types of connectivity to consider are:

Short Range: Includes Bluetooth, Zigbee, Ultra-Wideband, WiFi, and LoRa.

Wide Area Network: Includes 4G, 5G, Sigfox, Satcom, and Wired connection

IoT Platforms

An IoT platform engages all the elements of the IoT collection together; however, there is no one-size-fits-all perspective to IoT platforms.

Before selecting a platform, evaluating your options from different viewpoints, including considerations for proper technology selection and customizability under the IoT platform, is essential. The appropriate IoT platform for your business should, at a minimum:

  • It connects all of your hardware, including indicators and gadgets
  • Manage different hardware and software communication agreements
  • Provide security factors for devices and followers
  • Collect, anticipate and analyze data the sensors and devices gather under the IoT platform
  • Combine with your business procedures, applications, and web services under IoT solutions

Data management

The rate of data is at the center of every IoT solution. Data drives decisions, generates revenue, decreases costs, and improves quality under the IoT platform.

To that conclusion, there are eight data planning applications to keep in mind when composing your IoT data management version:

Derived insight reply time: How immediately do you require insight from the indicator? The solution will help determine the supporting framework you need to meet your insight needs.

Data collection: IoT framework often serves as the nucleus to combine data from multiple sensors – and this data must be modeled and processed to achieve your desired outcome under the IoT platform.

Data modeling is required to normalize this data across all stages and sensor categories.

Data quality: The life period of the sensor should be observed to ensure that time-conscious and reliable data is captured and expressed under IoT solutions.

Data transport: Data transport can significantly impact the ROI of your IoT activity. The more data you transfer, the more it will charge in bandwidth, computing, and storage under the IoT platform.

Data storage: There are multiple alternatives in data storage and several locations to store and calculate data, including on-prem, on-edge, or in the cloud.

Data processing: This is where standardization, filtering, and enriching of the data occurs. As each solution varies, so will your data processing need under the IoT platform.

Data governance: Your governing model should include how the data is captured and whether it is united or filtered as part of the process.


IoT applications are limited only by your imagination and ingenuity, but patterns are growing around typical uses and verticals for this technology under the IoT platform. Some examples of applications include:

  • Collecting operational data
  • Real-time asset monitoring
  • Tracking customer behavior
  • Location tracking
  • Machinery sensors
  • Fleet management

One use case may fit multiple IoT categories, allowing multiple vertical entries, IoT categories, and horizontal markets with a single application under the IoT platform.