This paper presents an AI-driven IoT robotic teleoperation system designed for real-time remote manipulation and intelligent visual monitoring, tailored for smart city applications. The architecture integrates a Flutter-based cross-platform mobile interface with MQTT-based control signaling and WebRTC video streaming via the LiveKit framework. A YOLOv11-nano model is deployed for lightweight object detection, enabling real-time perception with annotated visual overlays delivered to the user interface. Control commands are transmitted via MQTT to an ESP8266-based actuator node, which coordinates multi-axis robotic arm motion through an Arduino Mega2560 controller. The backend infrastructure is hosted on DigitalOcean, ensuring scalable cloud orchestration and stable global communication. Latency evaluations conducted under both local and international VPN scenarios (including Hong Kong, Japan, and Belgium) demonstrate actuator response times as low as 0.2 seconds and total video latency under 1.2 seconds, even across high-latency networks. This low-latency dual-protocol design ensures responsive closed-loop interaction and robust performance in distributed environments. Unlike conventional teleoperation platforms, the proposed system emphasizes modular deployment, real-time AI sensing, and adaptable communication strategies, making it well-suited for smart city scenarios such as remote infrastructure inspection, public equipment servicing, and urban automation. Future enhancements will focus on edge-device deployment, adaptive routing, and integration with city-scale IoT networks to enhance resilience and scalability.

This conceptual analysis examines the dynamics of data transmission in 5G networks. It addresses various aspects of sending data from cameras and LiDARs installed on a remote-controlled ferry to a land-based control center. The range of topics includes all stages of video and LiDAR data processing from acquisition and encoding to final decoding, all aspects of their transmission and reception via the WebRTC protocol, and all possible types of network problems such as handovers or congestion that could affect the quality of experience for end-users. A series of experiments were conducted to evaluate the key aspects of the data transmission. These include simulation-based reproducible runs and real-world experiments conducted using open-source solutions we developed: "Gymir5G" - an OMNeT++-based 5G simulation and "GstWebRTCApp" - a GStreamer-based application for adaptive control of media streams over the WebRTC protocol. One of the goals of this study is to formulate the bandwidth and latency requirements for reliable real-time communication and to estimate their approximate values. This goal was achieved through simulation-based experiments involving docking maneuvers in the Bay of Kiel, Germany. The final latency for the entire data processing pipeline was also estimated during the real tests. In addition, a series of simulation-based experiments showed the impact of key WebRTC features and demonstrated the effectiveness of the WebRTC protocol, while the conducted video codec comparison showed that the hardware-accelerated H.264 codec is the best. Finally, the research addresses the topic of adaptive communication, where the traditional congestion avoidance and deep reinforcement learning approaches were analyzed. The comparison in a sandbox scenario shows that the AI-based solution outperforms the WebRTC baseline GCC algorithm in terms of data rates, latency, and packet loss.

In this work, we tackle the problem of bandwidth estimation (BWE) for real-time communication systems; however, in contrast to previous works, we leverage the vast efforts of prior heuristic-based BWE methods and synergize these approaches with deep learning-based techniques. Our work addresses challenges in generalizing to unseen network dynamics and extracting rich representations from prior experience, two key challenges in integrating data-driven bandwidth estimators into real-time systems. To that end, we propose Merlin, the first purely offline, data-driven solution to BWE that harnesses prior heuristic-based methods to extract an expert BWE policy. Through a series of experiments, we demonstrate that Merlin surpasses state-of-the-art heuristic-based and deep learning-based bandwidth estimators in terms of objective quality of experience metrics while generalizing beyond the offline world to in-the-wild network deployments where Merlin achieves a 42.85% and 12.8% reduction in packet loss and delay, respectively, when compared against WebRTC in inter-continental videoconferencing calls. We hope that Merlin's offline-oriented design fosters new strategies for real-time network control.

In this time of pandemic, the world has turned to Internet-based, real-time communication (RTC) as never before. The number of RTC products has, over the past decade, exploded in large part because of cheaper high-speed network access and more powerful devices, but also because of an open, royalty-free platform called WebRTC. In fact, over the past year, there has been a 100-fold increase of video minutes received via the WebRTC stack in the anonymous population that has opted into Google Chrome's statistics. WebRTC can be found in most Internet meeting services, social networks, live-streaming experiences, and even cloud-based gaming products. An open source implementation and tutorials for this platform can be found at https://webrtc.org.

Google announced a giant slew of updates to its various software products at its I/O developer conference this week, and in addition to Android, Wear, Assistant and a ton of other news, it's not forgetting about the smart home. At the show, the company shared a few updates around its Nest and Android products that focus on a commitment to the recently renamed Matter ecosystem. As a recap, Matter was formerly known as Project CHIP, or Connected Home over IP. It's a collaboration between industry giants like Google, Amazon, Apple, Samsung and more to standardize the historically fragmented smart home ecosystem. Matter will support a variety of protocols and assistants, including Siri, Alexa, the Google Assistant as well as Bluetooth, Ethernet, WiFi and Thread.

Digital Universe is expanding and how! Each day marks a new entry in the burgeoning list of technologies that augment and innovate the way we interact with information. This rising digital consumption brings with it, untapped opportunities for a digital marketer to reach clients. We have compiled a list of three emerging opportunities that cannot be ignored anymore. Artificial Intelligence (AI) is a two-pronged tool to automate and augment your sales and boost lead conversion.

What Does Machine Learning Have to do with MOS Scores? Human subjectivity in MOS calculations doesn't hold water when it comes to heterogeneous environments. That's where machine learning comes to play. You get a voice call. You want to know its quality.

The workforce is evolving as organizations focus their efforts on digital transformation strategies. New approaches to technology are influencing employee productivity and collaboration. Five key technology trends are expected to drive the evolution of digital workforces in 2018. Irwin Lazar of Nemertes Research predicts the 6 collaboration trends we will see this year, and then we expand on some of those in this exclusive e-guide. Don't miss out on key UCC opportunities – become a member now and get this complimentary download.

Cloud Technologies have drastically evolved over the years paving way for businesses to communicate better with their customers. With each passing year, Cloud Technologies have undergone various transformations and advanced exponentially to meet varying business needs. As we progress to 2018, we bring the big players in the business landscape for the upcoming year. Chatbots like Salesforce Einstein and SAP Leonardo are giving major goals to rising significance of artificial intelligence. With everyone right from the beginners to the experts using bots like Siri, Cortana and Alexa vouch for the ease they bring in to the existing system.

All the hype in technology these days is around ML, AI/deep learning, self-driving cars, blockchain, AR/VR and other shiny new things. However, there is one area of technology that has been silently evolving and gaining momentum recently: communications. Comms no longer simply consists of things like PSTN, SIP or conference software and hardware. Its rise over time has been fueled by things like smartphones, social apps, productivity/collaboration apps, gaming and, more broadly, millennials. Even the big four tech giants -- Google, Apple, Facebook and Amazon -- have caught up to this and are spearheading some keys efforts in the field of communications.