-- This paper details four principal challenges encountered with machine learning (ML) damage assessment using small uncrewed aerial systems (sUAS) at Hurricanes Debby and Helene that prevented, degraded, or delayed the delivery of data products during operations and suggests three research directions for future real-world deployments. The presence of these challenges is not surprising given that a review of the literature considering both datasets and proposed ML models suggests this is the first sUAS-based ML system for disaster damage assessment actually deployed as a part of real-world operations. The sUAS-based ML system was applied by the State of Florida to Hurricanes Helene (2 orthomosaics, 3.0 gigapixels collected over 2 sorties by a Wintra WingtraOne sUAS) and Debby (1 orthomosaic, 0.59 gigapixels collected via 1 sortie by a Wintra WingtraOne sUAS) in Florida. The same model was applied to crewed aerial imagery of inland flood damage resulting from post-tropical remnants of Hurricane Debby in Pennsylvania (436 orthophotos, 136.5 gigapixels), providing further insights into the advantages and limitations of sUAS for disaster response. The four challenges (variation in spatial resolution of input imagery, spatial misalignment between imagery and geospatial data, wireless connectivity, and data product format) lead to three recommendations that specify research needed to improve ML model capabilities to accommodate the wide variation of potential spatial resolutions used in practice, handle spatial misalignment, and minimize the dependency on wireless connectivity. These recommendations are expected to improve the effective operational use of sUAS and sUAS-based ML damage assessment systems for disaster response.

Raspberry Pi has announced the Pico 2 W, a wireless version of its Pico 2 microcontroller board built for hobbyists and industrial applications. At 7, it's a relatively inexpensive way to control electronic devices like smart home gadgets and robots. With the new version, users will be able to securely link to remote sources to send and receive data, either via Bluetooth 5.2 or Wi-Fi 802.11n. As with the Pico 2, the wireless variant is built around the RP2350 microcontroller built in-house by Raspberry Pi. it offers more speed and memory than the original RP2040 chip, along with a security model built around Arm's TrustZone for Cortex-M. Users can program it using C, C and MicroPython, and choose between Arm Cortex-M33 or RISC-V cores.

This work introduces a solution to enhance human-robot interaction over limited wireless connectivity. The goal is toenable remote control of a robot through a virtual reality (VR)interface, ensuring a smooth transition to autonomous mode in the event of connectivity loss. The VR interface provides accessto a dynamic 3D virtual map that undergoes continuous updatesusing real-time sensor data collected and transmitted by therobot. Furthermore, the robot monitors wireless connectivity and automatically switches to a autonomous mode in scenarios with limited connectivity. By integrating four key functionalities: real-time mapping, remote control through glasses VR, continuous monitoring of wireless connectivity, and autonomous navigation during limited connectivity, we achieve seamless end-to-end operation.

The internet of things (IoT) is a huge market, with a forecast of 23.6 billion connections by 2026, according to ABI Research. This growth entails a wide range of devices and applications, opening up opportunities for different wireless connectivity technologies, improved security, and enhanced features with artificial intelligence. This month's issue covers all of it: wireless technologies, security, and AI in IoT. The Eclipse Foundation's 2021 IoT & Edge Developer survey revealed that the top three concerns of IoT developers are security, connectivity, and deployment. The significant increase in both security and connectivity concerns highlights the challenges that developers face in determining the right technologies for their applications, according to the report.

The gaming console turns 50 this year and is proving more popular than ever. Computer chips will remain in short supply this year and into the next, although not as acutely as in 2021, and video subscription services will see 150-million subscriptions cancelled worldwide, representing a market churn of about 30%, as competition intensifies. These are some of the findings in the Deloitte Global Technology, Media and Telecommunications (TMT) 2022 predictions, launched recently. The report, now in its 21st year, also foresees an explosion in the adoption of wearable health technology and apps, shows why Africa will lag the globe in the adoption of the new generation of Wi-Fi technology, Wi-Fi 6, but also why the continent can lead the way in reducing emissions from smartphones. "The report identifies which global TMT trends are most likely to impact businesses and consumers in the coming year," says Mark Joseph, TMT Leader for Deloitte Africa.

While the name may sound familiar thanks to Carl Pei's new audio brand Nothing that just launched a pair of true wireless earbuds, Omthing is looking to bring affordable luxury audio products to the country. The company is eyeing a 5% share of India's smart wearables market in 3 yrs and is also looking to set up an R&D centre in India. All three products come with a premium design and an IPX4 rating for dust and water resistance. The Omthing AirFree Lace Neckband is available in black colour option and priced at Rs 1,499 is the cheapest of the three. Omthing AirFree TWS earbuds will retail at Rs 2,499 and are also available in black colour only.

A computer vision technology developed by University of Cambridge engineers has now been integrated into a free mobile phone app for regular monitoring of glucose levels in people with diabetes. The app uses computer vision techniques to read and record the glucose levels, time and date displayed on a typical glucose test via the camera on a mobile phone. The technology, which doesn't require an internet or Bluetooth connection, works for any type of glucose meter, in any orientation and in a variety of light levels. It also reduces waste by eliminating the need to replace high-quality non-Bluetooth meters, making it a cost-effective solution. Working with UK glucose testing company GlucoRx, the Cambridge researchers have developed the technology into a free mobile phone app, called GlucoRx Vision.

When my son was a toddler, he went to his pediatrician for a routine CAT scan. He'd be awake and finished in a jiffy. He lay there on the clinic table, unresponsive, his vitals slowly falling. The clinic had no ability to diagnose his condition. Five minutes later, he was in the back of an ambulance.

What is the smart factory? In simple terms, it is the aspirational concept of a digitally transformed factory or warehouse. It is a cyber-physical ecosystem of virtualized and connected assets, people, and processes that constitute the manufacturing platform of the 4th industrial revolution that is Industry 4.0. One of the great expectations of 5G is that it will bring a new level of flexibility to the shop floor of a Smart Factory, allowing a growing number and range of mobile autonomous robots and vehicles to safely operate and coexist with humans in a manufacturing environment. The net expected outcome is the transition of today's static production models toward highly dynamic and software-defined production models.

The Internet of Things (IoT) is set to spread into every area of the enterprise over the next year, in order for that to happen it will need to start employing some of the newer, emerging technologies. This will be particularly true of Industrial IoT (IIoT) as more and more organizations start using the opportunities it offers to achieve business goals. Frank Vella, COO of Information Builder, points out that with the emergence of smart cities and new manufacturing processes, for example, there is a growing need for large pools of data. This data will be used to build more efficient, broader ecosystems that provide proactive insights in verticals like manufacturing, health and safety. "AI [artificial intelligence], predictive analytics, IoT and blockchain are all technologies that require strong data capture and use. Consequently, the way data is accessed will change to enable broader visibility and create cohesive ecosystems that support a convergence of data access and provides better operational and predictive capabilities," Vella said.