AI influence on IoT developers and their working installations
Wpisy
At the Consumer Electronics Show 2020, Arduino has made a possibly groundbreaking announcement with the Arduino Pro IDE. This could bring the maker scene and classic industrial companies closer together.
Arduino Portenta H7 features
The Portenta H7 is equipped with an STM32H747Xi with a Cortex-M7 and a Cortex-M4. Portenta H7 has 2 megabytes of RAM and a 16 MByte NOR flash. An SD card can be connected via an adapter. The connection to a wireless network is via WiFi 802.11 b/g/n or Bluetooth 5.1. The charging electronics for a 3.7 volt LiPo battery are already integrated.
With the Arduino Portenta H7, the first model of the new Portenta family was announced. This should be tailored specifically to the needs of industrial applications, AI and robotics scenarios.
The model is equipped with two 80-pin connectors, plus four UART ports. USB Type-C port can output image signals via DisplayPort. The Portenta H7 is also programmable with an interpreter in MicroPython, JavaScript and TensorFlow Light. The single-platinum calculator should be available from February for 90 euros.
Source: https://www.linuxinsider.com/story/86448.html
What the world says about Arduino Portenta?
Fabio Violante, CEO of Arduino, said manufacturers will be able to create modules for robotics, 3D printer and more:
Portenta H7 is directly compatible with other Arduino libraries and offers new features that will benefit hardware manufacturers, such as a DisplayPorl output, much faster ADC multi-channel and high-speed timers.
Meanwhile, Charlene Marini, vice president of strategy for Arm’s IoT Services Group commented:
SMEs with industrial requirements require simplified development through secure development tools, software and hardware to economically realize their IoT use cases.
ARM Partnership cooperation
ARM works with Arduino to provide secure, easy-to-manage and manageable devices to a wide range of programmers. Two innovations to date show the results of this partnership.
„Mbed OS Portenty is one of the concrete achievements of the partnership,” said Marini. „Another example is the Arduino SIM card, which uses Pelion connection management.”
She said companies have the ability to provide secure Internet of Things on a large scale. This is the foundation of machine learning, automation and the rapid evolution of applications that cross the physical and digital world.
Industrial use of Arduino-like solutions
One of industrial IoT devices, supporting Arduino-like technology is eModGATE from TECHBASE. Economical, ESP32-based solution can serve as an end-point in any installation or works well as a gateway, gathering data from scattered sensor mesh across the installation. For more information check Industrial IoT Shop with all the configuration options for eModGATE.
The latest research results from IoT Newark developers reveal that 49% of respondents use AI in their IoT applications. There is also a growing concern about user privacy and the more frequent introduction of ready equipment.
35% of respondents think security is the major concern for any IoT implementation, mainly due to the type of data collected from the things (machines) and humans, which is very sensitive & personal. We can expect to see more and more encryption everywhere. Businesses who initiate IoT projects treat IoT security as their top priority.
SBCs the main platform for Industrial IoT
SBC is still the preferred hardware foundation for IoT gates, then 54%, followed by personal projects (30%) and silicon supplier platforms (13%). It is unclear whether the latter includes a commercial computing module. As shown in the graph above, many IoT programmers need third party help, especially for edge-to-cloud communication.
About 45% of respondents use environmental sensors for IoT devices, followed by motion sensors (26%) and optical / image sensors (15%). WiFi (67%) is the most popular wireless technology in Internet of Things projects. The next places are Low cellular energy and Bluetooth, followed by LoRa at 21%. The survey results also include responses to programming languages, cloud platforms, IoT data, project motivation and more.
Artificial Intelligence influencing Industrial IoT
From the end of 2017 to 2018, artificial intelligence-specific processors (AI) began to appear on mobile devices. The goal is to make smartphones more intelligent. As GPUs shrink, AI-related equipment becomes necessary for the Internet of Things.
Support for enterprises from platforms such as Google TensorFlow will be introduced in 2020 with equipment adapted to artificial intelligence. TensorFlow is already optimized for mobile devices and can be quickly launched on single-board computers. In many ways, AI frameworks are better than other mobile frameworks, such as ReactJS. The AI structure is not designed to work with the user interface. It’s perfect for the Internet of Things.
Until the end of 2020, artificial intelligence will be as important for IoT devices as the cloud.
Hyperautomation is a process in which businesses automate as numerous commerce and IT forms as conceivable utilizing apparatuses like AI, machine learning, event-driven computer program, mechanical process automation, and other sorts of choice prepare and task automation instruments.
It is the key to both computerized operational greatness and operational resiliency for organizations. To empower this, organizations had to digitize their documents/artifacts and guarantee their trade and IT process workflows were advanced. They got to mechanize tasks, processes and coordinate computerization over utilitarian zones.
Hyperautomation is irreversible and inevitable. Everything that can and should be automated will be automated.
Brian Burke, Research Vice President, Gartner
Gartner prepared a Tech Trends 2021 summary with key features of the constantly changing market. Read more at: https://www.gartner.com/en/information-technology/trends/top-strategic-technology-trends-iot-gb-pd
Industrial IoT market evolution
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.
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.
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.
The latest research results from IoT Newark developers reveal that 49% of respondents use AI in their IoT applications. There is also a growing concern about user privacy and the more frequent introduction of ready equipment.
35% of respondents think security is the major concern for any IoT implementation, mainly due to the type of data collected from the things (machines) and humans, which is very sensitive & personal. We can expect to see more and more encryption everywhere. Businesses who initiate IoT projects treat IoT security as their top priority.
SBCs the main platform for Industrial IoT
SBC is still the preferred hardware foundation for IoT gates, then 54%, followed by personal projects (30%) and silicon supplier platforms (13%). It is unclear whether the latter includes a commercial computing module. As shown in the graph above, many IoT programmers need third party help, especially for edge-to-cloud communication.
About 45% of respondents use environmental sensors for IoT devices, followed by motion sensors (26%) and optical / image sensors (15%). WiFi (67%) is the most popular wireless technology in Internet of Things projects. The next places are Low cellular energy and Bluetooth, followed by LoRa at 21%. The survey results also include responses to programming languages, cloud platforms, IoT data, project motivation and more.
Artificial Intelligence influencing Industrial IoT
From the end of 2017 to 2018, artificial intelligence-specific processors (AI) began to appear on mobile devices. The goal is to make smartphones more intelligent. As GPUs shrink, AI-related equipment becomes necessary for the Internet of Things.
Support for enterprises from platforms such as Google TensorFlow will be introduced in 2020 with equipment adapted to artificial intelligence. TensorFlow is already optimized for mobile devices and can be quickly launched on single-board computers. In many ways, AI frameworks are better than other mobile frameworks, such as ReactJS. The AI structure is not designed to work with the user interface. It’s perfect for the Internet of Things.
Until the end of 2020, artificial intelligence will be as important for IoT devices as the cloud.
At the Consumer Electronics Show 2020, Arduino has made a possibly groundbreaking announcement with the Arduino Pro IDE. This could bring the maker scene and classic industrial companies closer together.
Arduino Portenta H7 features
The Portenta H7 is equipped with an STM32H747Xi with a Cortex-M7 and a Cortex-M4. Portenta H7 has 2 megabytes of RAM and a 16 MByte NOR flash. An SD card can be connected via an adapter. The connection to a wireless network is via WiFi 802.11 b/g/n or Bluetooth 5.1. The charging electronics for a 3.7 volt LiPo battery are already integrated.
With the Arduino Portenta H7, the first model of the new Portenta family was announced. This should be tailored specifically to the needs of industrial applications, AI and robotics scenarios.
The model is equipped with two 80-pin connectors, plus four UART ports. USB Type-C port can output image signals via DisplayPort. The Portenta H7 is also programmable with an interpreter in MicroPython, JavaScript and TensorFlow Light. The single-platinum calculator should be available from February for 90 euros.
Source: https://www.linuxinsider.com/story/86448.html
What the world says about Arduino Portenta?
Fabio Violante, CEO of Arduino, said manufacturers will be able to create modules for robotics, 3D printer and more:
Portenta H7 is directly compatible with other Arduino libraries and offers new features that will benefit hardware manufacturers, such as a DisplayPorl output, much faster ADC multi-channel and high-speed timers.
Meanwhile, Charlene Marini, vice president of strategy for Arm’s IoT Services Group commented:
SMEs with industrial requirements require simplified development through secure development tools, software and hardware to economically realize their IoT use cases.
ARM Partnership cooperation
ARM works with Arduino to provide secure, easy-to-manage and manageable devices to a wide range of programmers. Two innovations to date show the results of this partnership.
„Mbed OS Portenty is one of the concrete achievements of the partnership,” said Marini. „Another example is the Arduino SIM card, which uses Pelion connection management.”
She said companies have the ability to provide secure Internet of Things on a large scale. This is the foundation of machine learning, automation and the rapid evolution of applications that cross the physical and digital world.
Industrial use of Arduino-like solutions
One of industrial IoT devices, supporting Arduino-like technology is eModGATE from TECHBASE. Economical, ESP32-based solution can serve as an end-point in any installation or works well as a gateway, gathering data from scattered sensor mesh across the installation. For more information check Industrial IoT Shop with all the configuration options for eModGATE.
How to understand Internet of Things phenomenon?
The term Internet of Things is used to describe physical objects that have sensors that enable data acquisition and communicate with each other and the Internet. They belong to the following categories:
- Wearable sensors – sensors built into clothing or smartphones and smart watches
- Medical parameter sensors for monitoring health
- Sources of geoinformation, allowing to determine the location of objects and people
- Sensors of physical parameters of the environment, e.g. temperature, pressure, insolation, dust
- Sensors for the operation of technical devices, e.g. measuring power consumption, performance, including specialized sensory networks in industrial installations.
Other factors that contribute to the popularity of IoT are the versatility of use (e.g. intelligent buildings and cities, healthcare, trade, sport) as well as the benefits obtained through their implementation, e.g. streamlining the delivery process, loss prevention, and improving customer experience. Therefore, we can expect a growing number of new IoT solutions appearing on the market for various sectors. Gartner estimates that IoT product and service providers will generate growing revenue of $300 billion in 2020.
The Internet of Things (IoT) has rapidly become one of the most familiar — and perhaps most hyped — expressions across business and technology. We expect to see 20 billion internet-connected things by 2020. These “things” are not general-purpose devices, such as smartphones and PCs, but dedicated-function objects, such as vending machines, jet engines, connected cars and a myriad of other examples. The IoT will have a great impact on the economy by transforming many enterprises into digital businesses and facilitating new business models, improving efficiency and increasing employee and customer engagement.
Source: Gartner, https://www.gartner.com/imagesrv/books/iot/iotEbook_digital.pdf
With new possibilities, new challenges arise, such as the creation of an unprecedented amount of data. According to Oracle, there will be 40 trillion GB of IoT data by 2020.
Open source IoT solutions rushing gaining market
Referring to the results of the 2016 Future of Open Source Survey conducted by Black Duck and North Bridge, 65% of companies increased the use of open source solutions in 2016 compared to 2015. Not only small and medium enterprises use open source solutions. Open source solutions and technologies are used by large international corporations. They see no need to pay for solutions and services that they can use virtually free. Employing only people with appropriate qualifications.
Large corporations are not interested in paying for server logos, network devices, or mass storage. Instead of buying equipment from well-known suppliers, they prefer to set up an order in companies in East Europe and Asia. Companies where devices are designed and assembled (ODM original-design manufacturers).
Software-as-a-Service will be standard
As for IoT application trends, Software-as-a-Service is seen as a hot topic of discussion. SaaS is a service model. In this model, the service provider provides the desired application and makes it available to clients via the Internet. This helps organizations to outsource IT applications.
These Internet of Things trends provide companies with a marketing platform to promote their products. To this end, Stewart Butterfield, co-founder of Slack, a cloud-based instant messaging platform, said:
Every interaction with the customer is a marketing opportunity. When you go beyond the customer service page, people are more likely to recommend you.
SaaS is the preferred choice for the IT gaming industry due to the low investment cost. The emergence of SaaS has significantly contributed to the development of technology. When this trend of the Internet of Things appears on the market, people’s lives are better than ever.
Artificial Intelligence influencing Industrial IoT
From the end of 2017 to 2018, artificial intelligence-specific processors (AI) began to appear on mobile devices. The goal is to make smartphones more intelligent. As GPUs shrink, AI-related equipment becomes necessary for the Internet of Things.
Support for enterprises from platforms such as Google TensorFlow will be introduced in 2020 with equipment adapted to artificial intelligence. TensorFlow is already optimized for mobile devices and can be quickly launched on single-board computers. In many ways, AI frameworks are better than other mobile frameworks, such as ReactJS. The AI structure is not designed to work with the user interface. It’s perfect for the Internet of Things.
Until the end of 2020, artificial intelligence will be as important for IoT devices as the cloud.