Avnet Merges IoT Hardware and Software with Softweb Acquisition
The Engineer posted on May 15, 2019 |

With the proliferation of embedded control systems and the Internet of Things (IoT), the boundary between hardware and software is becoming blurred. The complex interplay of machine and code requires engineers to have proficiency in both electronics and programming. To expand its presence in the IoT market, Avnet, a long-time provider of electronic components and technology solutions, recently acquired Softweb Solutions, whose artificial intelligence (AI) software and data services will complement Avnet's hardware expertise, creating a more robust design, development and deployment system of product lifecycle management.

Avnet CEO Bill Amelio. (Image courtesy of Avnet.)

Avnet CEO Bill Amelio. (Image courtesy of Avnet.)

“By capitalizing on our longstanding partnership with Softweb, we are adding new capabilities to Avnet’s already robust ecosystem—combining the power of their software expertise with the strength of our end-to-end hardware ‘design to deploy’ ecosystem,” said Avnet CEO Bill Amelio. “Softweb’s formidable IoT and data platforms, plus their expertise in AI, data advisory and digital development services, will enable us to bring even greater value to our customers as a single partner resource while accelerating Avnet’s growth.”

A Unified Solution

If you've ever tried to install a unique, specialized interface card into a personal computer, then you've probably experienced issues that required calls to tech support. The device manufacturer will tell you that its hardware and drivers have been fully tested, so the problem must be with your computer or its operating system. The computer company will mostly likely blame the unique device that you're trying to install, with the bidirectional finger-pointing leaving you, the customer, to solve the problem through trial and error.

On the design side, it makes sense for IoT developers to work with a single vendor that handles both the hardware and software aspects of the project, end to end. Avnet's services help its customers develop business models for IoT-based products, assist with design and manufacturing, provide secure cloud-based storage and analytics, and offer insights into maintenance, repair and refurbishment. The company's engineers will partner with a client, essentially becoming an extension of the customer's design team, letting the client focus on its core product while leaving the IoT aspect to the experts.

Developing an IoT Strategy

IoT opens up a world of possibilities, including connected appliances, smart power grids, fleet deployment, asset monitoring, and industrial optimization. It also enables companies to deliver their products as services under a new business model. A manufacturer may be well versed in hardware, software and fabrication, but the ins and outs of cloud-based products and business models—including communication, security and data analytics—are best left to the experts, so many companies are choosing to partner with IoT providers like Avnet.

Connecting a product to the Internet creates complications with design, manufacturing and maintenance. Adding sensors and communication hardware to the device may increase its form factor and power requirements. These design and manufacturing challenges can be offset by the shift from preventative maintenance to predictive maintenance, which is made possible by sensors that constantly measure the physical aspects of a device and send those parameters to a portal, where software can determine whether a component failure is imminent. Parts can be replaced just in time rather than on a regular schedule based on a statistical model, saving money and reducing downtime.

Predictive Maintenance and IoT. (Image courtesy of Avnet.)
Predictive Maintenance and IoT. (Image courtesy of Avnet.)

IoTConnect Platform

The power of the IoT lies in its ability to monitor and control products in realtime and to extract data that enables engineers to optimize processes that involve those products. At the machine level, a robot can be outfitted with sensors that measure forces, strains and movements. This information is used in predictive maintenance, informing technicians when a component may be about to fail. On a more holistic level, data analytics coupled with machine learning algorithms can provide insights that help industrial engineers design better layouts and processes that reduce a robot's movements, streamline a manufacturing operation, and improve overall efficiency.

Machine learning and data analytics. (Image courtesy of Avnet.)
Machine learning and data analytics. (Image courtesy of Avnet.)

Avnet's IoTConnect is an IoT hosting platform that provides engineers with data management tools such as transmission, storage, security and analysis. Rather than spending time and resources designing, implementing and maintaining a home-grown IoT system, companies can simply contract with an IoT platform provider, effectively outsourcing most aspects of their data management. In this scenario, the provider assumes responsibility for maintaining the servers, edge computers, communication links, firewalls, and malware protection, allowing the manufacturer to focus on getting its product to market and using data to improve its services. 

IoTConnect: A holistic IoT platform. (Image courtesy of Avnet.)
IoTConnect: A holistic IoT platform. (Image courtesy of Avnet.)

IoTConnect provides secure remote access from any connected device, such as a desktop computer, tablet or smartphone. Multiple layers of security help ensure that only authorized personnel can access the data and controls. Custom dashboards can be designed using a drag-and-drop interface, eliminating the need for coding in C++ or another programming language. Data is displayed as virtual meters, gauges, tables, charts or graphs—whatever is most appropriate for an effective human-machine interface (HMI).

Custom dashboard. (Image courtesy of Avnet.)
Custom dashboard. (Image courtesy of Avnet.)

IoT devices can communicate directly with one another, send real-time data to an edge computer or to the cloud, and respond to remote commands. They can also be programmed to instantly notify an engineer or technician in the event of a serious condition, such as a failed component or a safety breech. These relatively simple operations represent the entry-level stage of IoT, and the processes can be easily handled by low-end embedded controllers and inexpensive sensors. The connectivity of these devices, however, provides more than just communication; sending sensor data to more powerful computers located upstream and facilitates machine learning and AI, which can give engineers insights into the product's performance and enable them to improve its design.

Adding AI to the IoT. (Image courtesy of Avnet.)
Adding AI to the IoT. (Image courtesy of Avnet.)

Edge Computing and AI

When we think of AI, we tend to visualize cloud-based servers cranking out massive computations. The problems with that model are the latency associated with getting data to the cloud and, to a somewhat lesser extent, the bandwidth that the data consumes. These issues will only worsen as more devices become connected.

Latency is a problem with real-time applications. (Image courtesy of Avnet.)
Latency is a problem with real-time applications. (Image courtesy of Avnet.)

The silver lining, so to speak, is that today's high-end embedded controllers, located right on the IoT devices, are powerful enough to run some basic AI computations, and edge-based computers—small servers stationed at local facilities—can do the bigger number crunching required by most AI and machine learning applications. This reduces the size of the pipeline needed for cloud communication and decreases latency, which is critical in many real-time applications. Small snapshots of data can be sent to a cloud-based server for in-depth analyses that don't need to be performed in realtime.

For example, a smart factory may have dozens of robots and CNC machines working on a single product. In addition to the sensors and communication that enable predictive maintenance on the individual machines, aggregated data from all the equipment can be analyzed in the cloud, with machine learning algorithms simulating multiple what-if scenarios. By recognizing patterns in the data, the cloud-based AI could recommend improvements in manufacturing processes, allowing the assembly line to be more productive and less costly to operate. As more data comes in, factory models can be refined, leading to continual improvement of the processes.

IoT Applications

On a factory floor, any machine or worker is considered an asset. Other examples of assets include fleet vehicles, construction equipment, distributed energy resources (wind, solar, storage), and more. Local and remote asset monitoring can lead to increased production, improved reliability, greater functionality, reduced energy consumption, and lower costs for both the consumer and the provider.

(Image courtesy of Avnet.)
(Image courtesy of Avnet.)

One application that might not be intuitively obvious is retail—more specifically, smart retail. In this case, IoT-based asset monitoring can help with inventory control, smart shelf technology, customer analysis, and personalization. A smart retail outlet is capable of delivering interactive content like coupons, new product announcements, and store maps to customers' phones. The retailer can gather insights into how customers are using this data, as well as gain an understanding about customers' shopping habits, the effectiveness of sales and other marketing promotions, and even the store layout.

Smart retail can improve the customer experience. (Image courtesy of Avnet.)
Smart retail can improve the customer experience. (Image courtesy of Avnet.)

Every facility—whether commercial, industrial, office or residential—can reduce operational expenses by employing energy management technology like Avnet's Smart Energy Monitoring Solution. Just as the IoT lets industrial engineers monitor manufacturing equipment and operations, energy management provides facility managers with the tools they need to optimize HVAC and lighting systems to reduce energy consumption while increasing comfort and productivity.

Energy management. (Image courtesy of Avnet.)
Energy management. (Image courtesy of Avnet.)

It's a Smart, Connected World

As engineers strive to improve products, enhance customer experiences, and increase efficiency, the role of IoT will continue to grow. Platforms like IoTConnect let companies augment their products with IoT features without having to invest in additional infrastructure or expertise. The old adage about business people is now true for machinery: it's good to be smart and connected.

Here's an overview of the IoTConnect platform:

(Video courtesy of Avnet.)


Avnet has sponsored this post.


Recommended For You