Orange Business’ Post

Neil Brown Ocean Sensors, Inc. (NBOSI) has launched its latest innovation ahead of Oceanology International 2024 in London. The new integrated CTD Sensor promises to redefine underwater data collection, addressing an increasing demand for smaller, more capable UUVs in various industries. 🌊 NBOSI is a pioneer in research-quality conductivity-temperature sensors for mobile marine platforms. 🛟 The UUV landscape is undergoing a transformative shift, driven by technological advancements, AI, and machine learning (ML). As vehicles are getting smaller, while growing in numbers and enhancing their capabilities, there is an increasing demand for compact, affordable, yet highly accurate sensors. This demand is unprecedented and continuously expanding. ⚓️ The integrated CTD sensor represents a leap forward in UUV technology, offering a compact, palm-sized design that provides research-quality temperature, salinity, depth, and sound speed measurements. Dr. Dave Fratantoni, NBOSI's CEO, highlights the advantages of the new sensor, emphasizing “simplified maintenance, faster recalibration, and superior data quality.” 🔗 Find out more >> https://hubs.la/Q02n8ZlB0 “As UUVs continue to shrink in size, NBOSI's compact sensors are poised to play a crucial role in meeting the industry's demands. The company's commitment to strategic focus and sensor versatility establishes NBOSI as a key player in the rapidly expanding UUV industry.” - Dr. Dave Fratantoni, NBOSI CEO. We are excited to see what NBOSI will showcase at Oi2024 👏 Read more on the Ocean Science & Technology website. #ocean #technology #Oi2024 #unmanned #sensors

Revolutionize transportation infrastructure with 𝗖𝘆𝘃𝗹.𝗮𝗶's data-driven solutions! 𝗖𝘆𝘃𝗹.𝗮𝗶, born from the vision of co-founder 𝗗𝗮𝗻𝗶𝗲𝗹 𝗣𝗲𝗹𝗮𝗲𝘇, is transforming the transportation infrastructure sector through advanced digital tracking. With a recent $6 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁, this 𝗕𝗼𝘀𝘁𝗼𝗻-𝗮𝗿𝗲𝗮 𝘀𝘁𝗮𝗿𝘁𝘂𝗽 leverages lidar, cameras, and sensors combined with geospatial AI to predict repair needs and create digital twins of infrastructure elements. Partnering with civil engineering firms to enhance data quality for municipalities, 𝗖𝘆𝘃𝗹.𝗮𝗶 is setting a new standard for how infrastructure is maintained, aiming for a future where every city benefits from smarter, more sustainable transportation systems. Stay tuned with us for the latest updates. 👉 For more information, visit this link: https://tcrn.ch/4aaWydE #innovation #infrastructure #smartcities #technews #trendingnews #techupdates

Very glad to announce that our recent paper, entitled "Stability and Accuracy-Aware Learning for Task Offloading in UAV-MEC-assisted Smart Farms," has been accepted for publication in #IEEE Transactions on Network and Service Management. Special thanks to Prof. Melike Erol-Kantarci for her assistance in conducting this research and handling the review process. I'm proud to collaborate with a great research group from #Nokia Bell Lab in Ottawa, including Dr. Sean Kennedy and Dr. Aisha Syed. The manuscript can be found via this link: https://lnkd.in/gdyNYEXE Abstract This study introduces an intelligent task offloading framework designed for smart farms that seamlessly integrates IoT devices, Unmanned Aerial Vehicles (UAVs), and Mobile Edge Computing (MEC) technology. At the heart of our methodology is the utilization of multi-agent reinforcement learning (RL) and Lyapunov theory to optimize task offloading decisions. Our primary contributions are ensuring system stability, task inference accuracy, and minimizing both task loss and delay. System stability is rigorously assessed by formalizing it based on the queue lengths of the MEC server, UAVs, and IoT devices. Furthermore, diverse machine learning (ML) models with varying complexities, such as different numbers of neurons or hidden layers, are deployed by the MEC server, UAVs, and IoT devices. This approach allows us to define task losses in relation to the inference error tolerance of the ML models. Our ultimate goal is to minimize UAV costs, taking into account energy requirements and error tolerance, all the while ensuring system stability. The growing stochastic optimization challenge, particularly with the increasing number of IoT devices, is addressed through the application of Lyapunov optimization theory and a stochastic game framework. However, due to the dynamic nature of the network environment, addressing the game proves to be a challenge, prompting us to develop and implement a multi-agent deep RL (DRL) approach. Our derived intelligent offloading scheme decreases the delay per task by about 35% with respect to the intelligent algorithm without jeopardizing the inference accuracy.

Curious about how AI and drones are transforming building envelope diagnostics and saving energy? Don’t miss the session led by Tarek Rakha "Seeing Beyond What's Visible: AI Envelope Diagnostics that Saves Building Energy" by Lamarr.AI. 🔍 What You’ll Learn: 1. What: How AI-powered computer vision drones and cloud computing can perform rapid, accurate building exterior diagnostics and energy audits. 2. Why: Discover how 20-40% of building energy can be saved using an innovative and cost-effective process for building façade inspections. 3. How: Learn how AI detects thermal leaks, water intrusion, and physical damage, offering precise solutions that outperform legacy audits. This session is a game-changer for #facilities managers looking to improve building performance, reduce energy costs, and streamline envelope #maintenance. Get insights on how to utilize cutting-edge technology for faster, cheaper, and more accurate diagnostics. 👉 Register now and see how AI can help you take your campus operations to the next level! #SRAPPA2024 #BuildingEnvelope #EnergyEfficiency #AI #DroneTechnology #FacilitiesManagement #Innovation #CostSavings

Trends from Digital Construction Week Conference: - Companies are witnessing a surge in geomapping and underground data analytics services, proving invaluable for infrastructure projects by providing critical insights. - Technology companies, especially SaaS providers, are integrating multiple processes into a single system to streamline operations and increase efficiency. CausewayOne is a prime example of this consolidation. - The expansion of drone surveillance for infrastructure assets is on the rise, including the innovative development of hydrogen-powered drones for enhanced surveillance capabilities and reduced carbon emissions. - Leveraging AI effectively can significantly boost productivity in the construction industry by optimizing project management, enhancing decision-making processes, and automating routine tasks. - Recruitment poses challenges and opportunities in the construction sector, with a growing demand for skilled professionals adept at utilizing new technologies. Companies must focus on attracting and retaining talent through competitive benefits and continuous learning opportunities. #digitalconstructionweek #BIM #DigitalTransformation #DCW2024

Radio connections for uncrewed systems are going through significant changes. Cognitive radio (CR) is increasingly being adopted, using software-defined radio (SDR) to analyse the local spectrum and find areas that are clear, reducing the power required and extending battery life. Mobile ad-hoc networks (MANETs) are being used with swarms of UAVs to enhance radio connectivity, sharing data about the spectrum across a wide area. New, lightweight antenna designs with multiple feeds and beamforming are also improving the performance of radio links in the air, allowing for longer range connections beyond the visual line-of-sight (BVLoS) or reducing the power needed for close work. Meanwhile, machine learning (ML) and artificial intelligence (AI) are being adopted in radio systems to boost cognitive architectures and the efficiency of connections, especially for high bandwidth video. At the same time, millimetre-wave radio technology (mmWave) is maturing to provide higher-bandwidth video links that are less susceptible to interference. The technology is maturing to be cost effective for vehicles on the ground and for high-altitude pseudo satellites (HAPS), where power is a critical consideration. Our thanks to... Radionor Communications AS Blu Wireless Filtronic Steatite Limited Read more ➡ https://lnkd.in/ezN4wZyw #uncrewedsystemstechnology #radio #telemetry #autonomousvehicles

Imagine an alternative coverage technology to the normal cellular one all mobile operators are using that would allow them to do without the costly and low-profitable rural cellular network they have today to satisfy their customers' expectations of high-quality ubiquitous cellular coverage. Back in 2015, I got involved with Deutsche Telekom AG Group Technology, under the leadership of Bruno Jacobfeuerborn (Group CTO DTAG at the time), in working out the detailed operational plans, deployment strategies, and, of course, the business case as well as general economics of building a stratospheric cellular coverage platform from scratch with the UK-based Stratospheric Platform Ltd in which Deutsche Telekom is an investor. The investment thesis was focused on the way we expected the stratospheric high-altitude platform to make a large part of mobile operators' terrestrial rural cellular networks obsolete and how it might strengthen mobile operator footprints in countries where rural and remote coverage was either very weak or non-existent. Where are we with Stratospheric mobile broadband coverage platforms almost ten years later? In my article, I include low-earth satellite coverage, a tangible option that exists today and receives a lot of interest (The Musk Effect?), comparing it with the potential of HAP-based broadband coverage, a technology that is still under development. A near-identical "digital twin" sister to my blog can be found at the New Street Research's Research repository, published together with James Ratzer and Russell Waller. I will link it in the comments section. https://lnkd.in/drMdedcG #StratosphericDrones #HAPS #LEOSatellites #D2D #D2C #5G #6G #TechnologyEconomics

In this paper, the authors propose a secure #short-#packet #communication (#SPC) system, where a #unmanned #aerial #vehicle (#UAV) serves as a mobile #decode-and-#forward (#DF) relay, periodically receiving and relaying small data packets from a remote IoT device to its receiver in two hops with strict latency requirements, in the presence of an eavesdropper. This system requires careful optimization of important design parameters, such as the coding blocklengths of both hops, transmit powers, and the UAV's trajectory. While the overall optimization problem is nonconvex, the authors tackle it by applying a #block #successive #convex #approximation (#BSCA) approach to divide the original problem into three subproblems and solve them separately. ---- Milad Tatar Mamaghani, PhD, Xiangyun (Sean) Zhou, Nan Yang, A. Lee Swindlehurst More details can be found at this link: https://lnkd.in/ddeZFn5v

In this article, the authors explore path optimization and transmission organization algorithms to minimize flight time and extend the range of #unmanned #aerial #vehicles (#UAVs) performing collaborative #federated #learning (#FL) among geographically dispersed nodes communicating through wireless connections offered by UAVs coupled with #device-#to-#device (#D2D) networks. The UAV orchestrates FL between spatially scattered homes via long-range radio wireless communication. They formulate the drone path optimization as a #traveling #salesman #problem (#TSP) and employ #self-#organizing #maps (#SOM) for path planning. Additionally, #knowledge #distillation (#KD)-based FL is used to reduce communication overhead for the resource-constrained UAV-#Internet #of #Things (#IoT) system. ---- Gad Gad, Aya Farrag, Ahmed Aboulfotouh, Khaled Bedda, Zubair Md Fadlullah, PhD, SM-IEEE, Mostafa M. Fouda More details can be found at this link: https://lnkd.in/esaNpzkM

💡 Korea University and Sookmyung Women's University researchers introduced a framework combining #quantum and classical computing to optimize drone fleet mobility control, addressing challenges like non-stationarity and scalability. QMDRL stands for Quantum Multi-Drone Reinforcement Learning, and it represents a significant leap forward in how we manage and deploy #drone #technology. By leveraging the unique strengths of both quantum and classical computing, this framework can solve complex optimization problems far more efficiently than traditional methods. This means more precise route planning, reduced #energy consumption, and enhanced collision avoidance, leading to safer and more reliable drone #operations. The applications of QMDRL are vast. In logistics, it can streamline delivery routes, ensuring faster and more efficient service. In #agriculture, it can optimize the monitoring and treatment of crops, leading to better yields and resource #management. In emergency response, it can enhance the coordination and effectiveness of search and rescue missions. In #insurance it can help reduce cost of claims handling. I believe you can imagine of more #apps. What do you #think? 🖼 The image below was generated by #artificial #intelligence to capture your attention.