In early July, I was honored to have a chat with Megha Daga, Senior Director of Product Management and AI/ML lead for the Internet of Things (IoT) at Qualcomm Technologies, Inc. . As a critical player in AI enablement across the IoT group at Qualcomm, Megha has been crucial in the development of cutting-edge AI solutions used around the world.
We dove right into what Qualcomm has been up to as it continues to advance IoT through the different core offerings, partnerships, and cutting-edge solutions that Qualcomm offers. To set the tone of our conversation, we discussed Edge AI.
Edge AI is essentially intelligence moving to the data generator, according to Megha. Along with getting data faster, a host of other factors impact Edge AI, including privacy, cost, latency, reliability, and bandwidth. For businesses or enterprises, the simplicity of the technology revolves around business intelligence occurring on the device or close to the device itself to enable IoT.
Qualcomm provides a portfolio of hardware technology, but even more exciting is their advancements in software design and embedded processing innovation. The company understands how heterogenous computing makes AI possible and is pushing the envelope to remain competitive in AI and IoT. Some of the stronger vertical markets and industries that Qualcomm is targeting include retail, logistics, energy, utilities, industrial, and robotics.
To further advance into AI, Qualcomm launched the Vision AI Development Kit. This Azure IoT Starter kit is a vision AI developer kit for running artificial intelligence models on devices at the intelligent edge. With Edge AI, data is generated and pushed to the cloud. Legacy devices such as retail payment terminals and other industry specific devices are being digitized and modernized. Hardware or devices can be connected to a box, i.e., edge gateway. Megha shared that Qualcomm is taking metadata and compute to the box, implementing further compute as needed, then sending only the required data back to the cloud. The traditionally “dumb” environment is becoming more intelligent and bringing efficiencies to businesses and operations. Another Qualcomm AI example outside of retail is in logistics, more specifically warehouse operations. Robotics and drones may be used for picking and dropping, reducing overall payloads, and therefore reducing costs.
Edge AI and IoT are coming together to minimize compute to the cloud, as the overall costs of sending massive data to the cloud is becoming more cost prohibitive, and a concern for larger enterprises. The issues of privacy, latency, and connectivity again remain important factors. Privacy not only affects consumers, it also impacts businesses and their customers’ experiences. As for latency, think of delivery robots on the street, providing sub-millisecond intelligence and information to enable operations and efficiency so consumers can get food, packages, products delivered (similar to same day delivery).
Regarding connectivity, especially for operations in remote locations (construction, agriculture), having on-device or near device data intelligence can be critical. Examples Megha mentioned included drones connected to a gateway to enable crop intelligence, construction management, and mining operations.
Qualcomm’s portfolio continues to evolve to support AI and Edge AI, with a stronger focus on software. Their hardware and chipsets will continue to be their foundation, as they grow their partnerships with Original Equipment Manufacturers (OEMs). Qualcomm is leading in the areas of enabling AI on traditional CPUs/DPUs or AI on SDKs. Another cutting-edge development includes AI on embedded processing (low power, high performance).
According to Megha, a few exciting AI areas that Qualcomm has been innovating around includes drone robots, and camera technology. Taking regular cameras for example and making them intelligent, using technologies such as machine vision and AI running on heterogenous computing to completely disrupt its capabilities. Megha shared that Qualcomm is using hardware accelerators for neural network workloads. Furthermore, AMR devices (autonomous mobile robots, i.e., Bosch devices) is an area where Qualcomm is developing chipsets and reference designs to further advance delivery. For example, they recently launched the RB6, a high-end chipset with an accelerator card allowing the robot to greatly improve throughput (i.e., delivery robots).
As far as software goes, Qualcomm is investing and innovating to provide seamless software across the Qualcomm AI stack. Qualcomm is providing unification for developer building and changes, using Qualcomm Intelligence multimedia SDKs providing authentication and simplification for development and deployment, across multiple verticals. Developers and software tools remain a top priority for Qualcomm. Qualcomm realizes the end-customer (businesses and government) require and need end-to-end solutions and thus continues to build out its IoT partner portfolio (vendors, integrators, industry focused providers) focused on software/applications, platforms, and other solutions
I’ll end with a great use case example shared by Megha. The Qualcomm AI Engine runs ML models in IoT devices, such as a security camera that recognizes a family member and activates a smart lock to allow entry. Or an office building that allows employees onto an elevator based on a touchpad. This context showcases the importance of how Qualcomm is advancing AI and IoT to prepare tomorrow’s businesses and cities.
For more reading, please check out, “Qualcomm Advances Development of Smarter and Safer Autonomous Robots for Logistics, Industry 4.0, and Urban Aerial Mobility with Next-Generation 5G and AI Robotics Solutions”
Written by Stephanie Atkinson, CEO of Compass Intelligence
Smart cities or intelligent cities are not only about technology improving city services, but they are about improving the community experience as you live, work, and play. Yes, much has changed over the past 18 months, but city projects are moving forward and with a boost of energy because of the pandemic and new funding sources. The industry as a whole is finding new project opportunities centered around automation, remote operations, contactless services, public health and safety, and new ways to deliver legacy services to avoid the face-to-face interaction for safety purposes. A few key technologies directly aiding in smart city initiatives include Internet of Things (sensors, connecting assets, tracking assets, real-time alerting or intelligence), mobile applications, augmented or virtual reality, artificial intelligence, and machine learning.
Historically, smart city projects have centered around traffic management, smart lighting, and city asset management, and while those areas are expected to continue to be areas of focus, new use cases are coming into the mix. Under the American Rescue Plan and Coronavirus Relief Fund (CARES ACT), cities and public schools are receiving emergency funding to support in projects related to safety, healthcare, and administering city services in new and safe ways.
READ MORE AT EXECUTIVE VIEWPOINT
A week ago, I sat down virtually with Brandon Branham, Chief Technology Officer and Assistant City Manager of Peachtree Corners (PTC, one of the first cities in the United States powered by real-world smart city infrastructure, which also features ‘Curiosity Lab at Peachtree Corners’) to get an update on all of the progress being made in making the city smarter, more interactive, and inviting to technology innovators around the globe. Peachtree Corners launched an innovative living smart city lab about 1 year back that leverages autonomous technology, IoT, AI, machine learning, edge computing, virtual reality, and other advanced technologies to advance city operations, mobility, and introduce economic development.
Some of the more interesting key facts about PTC include the following:
The innovation being embraced at PTC comes with the value it is placing in partnerships, leading technology company initiatives, and the live testing environment it provides to tech companies, OEMs, and startups around the globe. They currently have roughly 10 vendors with 15 different device types generating data across their network across around 15 or so different software systems. On the embracing of global companies, it is also working with a Tel Aviv company called IPgallery, that brings together city insights and intelligence using a real-time AI data platform that provides visualization (visual map) across PTC to monitor, analyze and secure all IoT devices across the ecosystem, buses, cameras, applications, etc. In addition, traffic flow and pattern data are being collected to adjust and make real-time rerouting decisions to improve public transportation.
PTC recently announced a partnership with Bosch, where they are implementing a sensor connected intersection and intelligent traffic management system to capture video including vehicle identification, vehicle recognition of objects (car, bus, scooters with drivers or without, pedestrians, etc. using machine vision). This partnership will allow real-time adjustments to traffic signaling, share the flow of traffic activity, and identify the type of vehicle in that flow for improved traffic management. PTC's Curiosity Lab will allow for a living city environment for Bosch to leverage its leading edge solution within a live, real municipality.
A few other projects on the horizon include the following:
All of these activities would not be anywhere without the public-private partnerships (3Ps) in place. PTC has a process to test in their live environment, receive funding from 3rd parties or commercial entities (for some projects), decide on whether the project is scalable, and then the city decides and will invest as needed. This is a prime example of how business and government can and should work together to advance the smart city vision.
On a final note, below is a list of key differentiators that enable PTC be the groundbreaking innovator in smart city solutions:
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