Industrial Internet of Things (Industrial IoT or just IIoT for short) uses Internet of Things technology to improve production and industrial processes. These processes increasingly require connected devices to perform their tasks effectively.
Data generated over the Internet of Things is growing exponentially faster than the traditional cloud environment where data is stored, so just the amount of data can justify the acceleration. In addition, in the cloud as the destination, problems related to data transfer (delay and bandwidth) occur, so travel speed is the main issue. This edge is necessary as a solution to the inefficiency of IIoT to Cloud architecture.
IIoT market predictions
Industrial IoT devices and edge computing have grown at impressive rates. Accenture predicts the IIoT market will reach $500 billion by 2020; and IIoT already generates 400 zetabytes a year. Gartner estimates that IoT currently generates about 10% of enterprise data; by 2022, Gartner has predicted this will increase to 50%.
According to IDC, IT’s annual investment on edge infrastructure will hit 18% of total IoT spending; and per last year’s Forrester Analytics Global Business Technographics Mobility Survey, 27% of global telecom decision-makers say their companies will either implement or expand edge computing this year.Source: https://www.cisco.com/c/en/us/solutions/internet-of-things/industrial-iot-devices.html
Perimeter (edge) computing architectures bring computing processing closer to the users and devices that need it, rather than centrally processing it in a local data center or public cloud. This edge is important for industrial and production processes that use large amounts of data that require fast response times and tight security.
Fast data processing of Industrial IoT devices
When industrial IoT devices and edge processing work together, digital information becomes more powerful. Especially in contexts where you need to collect data in a traditional edge context, such as a smart meter, a parking meter or a connected trash can in a street apartment. The installation of sensors with internet access in metropolitan garbage containers is becoming increasingly common for smart urban engineers. You can then remotely monitor the container using the sensor. When it is full, the city sanitation service receives a notification and can register an order and empty the container.
By introducing AI (artificial intelligence) into the device itself, edge computing can also make more context-sensitive, quick decisions at the edge. Data gathered from the sensors can be transferred to the cloud at any time after local work has been completed, contributing to a more global AI process, or archived. With the combination of industrial IoT devices and advanced technology, high quality analysis and small footprint will become the AI standard in 2020.
Latest innovations used in industrial solutions
One of many uses of IoT can be edge devices, dedicated to data management, process control (e.g. with MQTT protocol) and monitoring. Latest ESP32-based eModGATE controller from TECHBASE company is a series utilizing MicroPython environment to provide data management solutions for end-points applications. The eModGATE has built-in Wi-Fi/BT modem and can be equipped with additional NarrowBand-IoT, LoRa, ZigBee, etc.
For example eModGATE eqipped with wireless NB-IoT modem are perfect for industrial automation solutions, e.g. data logging, metering, telemetrics, remote monitoring, security and data management through all Industrial IoT applications.