Nancy Munro Single Presenter

It's mind-boggling how fast generative AI has spread across the world. Just recently the EU AI Council has placed guard rails on the use of this technology. How can organizations and individuals protect themselves against the miss-use of these AI-powered digital performers? In this presentation, Nancy Munro, CEO of Verbal Transactions will discuss the pros and cons to deep fakes and how to set up governance for internal and external uses.

Damien Stolarz Single Presenter

WebRTC has emerged as the primary protocol for the most demanding, ultra real-time video streaming scenarios, such as telepresence, conferencing, surveillance, and drone control. It has also found broad adoption in the media industries, including AAA game development, cinema, television and advertising as a collaboration tool.. In this session, we will go over how WebRTC is being used to enable various industry workflows, such as game development, remote direction, virtual sets (LED walls). We will also share lessons learned adapting WebRTC to professional/studio-grade audio and video standards.

Midam Kim, PhD Single Presenter
Polly Allen Single Presenter

Broad availability of Large Language Models is revolutionizing how conversational AI systems can interact with humans, yet the factors that influence user trust in conversational systems, especially systems prone to errors or ‘hallucinations’, remain complex and understudied. In this talk titled \\\\\\\"Trusting Unreliable Genius\\\\\\\", we delve into the nuances of trust in AI, focusing on trustability factors like competency, benevolence, and reliability. We begin by examining human conversation dynamics, including the role of interactive alignment and Gricean Maxims. These principles are then juxtaposed with Conversational AI interactions with several state-of-the-art LLM chabots, offering insights into how trust is cultivated or eroded in this context. We also shed light on the necessity for transparency in AI development and deployment, the need for continuous improvement in reliability and predictability, and the significance of aligning AI with user values and ethical considerations. Building trust in AI is a multifaceted process involving a blend of technology, sociology, and ethics. We invite you to join us as we unravel the complexities of trust in Conversational AI and explore strategies to enhance it.

Vladimir Beloborodov Single Presenter

For over two decades, GStreamer remains a "Swiss Army knife" when building applications and services producing or handling media data. With a big – and still growing – collection of processing elements, developers can construct fairly sophisticated pipelines for audio and video, tailored to their specific use-cases. In particular, GStreamer can be a viable option for many WebRTC-based designs; for instance, when implementing hardware-based acceleration for video encoding or decoding.While the modern GStreamer already offers several good options to integrate it with external software components. Doing so may still be challenging and time-consuming, especially if it is desirable to run and control GStreamer as a separate process that can efficiently exchange media data with the main application – rather than embedding it inside the application itself and customizing the basic "appsrc" and "appsink" elements. Such a separation may be preferable, or even mandatory, for a number of reasons: From better modularity and security to specific licensing-related considerations.This talk will present a new open-source tool that aims at greatly simplifying the task of integrating GStreamer with external software components: Enabling developers to quickly add it into their designs – while allowing to launch it as a separate process, easily modify and tweak its media processing pipeline without rebuilding the main application, and to efficiently exchange media data with it. Additionally, the presentation will briefly review a companion project that uses this new tool to facilitate quickly implementing hardware-accelerated media encoding or decoding on top of the widely-used WebRTC library from Google.

Neil Dwyer Single Presenter

Realtime audio and video content is typically created and consumed by humans. As compute has gotten cheaper, ML/AI technologies have become more accessible to application-level developers. Modern WebRTC SFUs have furthermore made it easier for application developers to read and write to media sessions without maintaining complicated and stateful infrastructure.These advancements have made easier than ever for media content to be consumed and created algorithmically, by software, to create experiences that go far beyond simple full duplex realtime media sessions. This talk will show real world examples of software as participant(s) in WebRTC sessions and how they were made.

Eric Burger Single Presenter

At a previous IPTcomm we presented the concept of using dynamic 5G network slicing to allocate resources for first responder emergency communications [1]. In the Commonwealth Cyber Initiative’s xG laboratory, we have leveraged our end-to-end open-source Open RAN test bed to prove out dynamic network slicing for first responders. This required cooperation between near real-time applications (rApps) and non-real-time applications (xApps) cooperating to provide the optimal allocation of guaranteed network bandwidth to first responders when they need it, and regular communications when they do not. We demonstrated this system in our live network with over 72 radios as well as taking it on the road to Mobile World Congress.[Researchers on this project: Aloizio DaSilva, Joao F. Santos, Jaswanth S. R. Mallu, Vikas Radhakrishnan, Prateek Sethi, Tapan Bhatnagar, Eric W. Burger, and Luiz A. DaSilva][1] Carlberg, K., Burger, E., and Jover, R., Dynamic 5G Network Slicing for First Responders, IPTComm 2019, Chicago, IL, USA, 15 October 2019, https://doi.org/10.1109/IPTCOMM.2019.8921240.

David vonThenen Single Presenter

Immerse yourself in the future of real-time video communications with a captivating live demonstration. Experience firsthand the seamless integration of ChatGPT with WebRTC, revolutionizing conversation understanding and response generation. Join us to witness the power of AI-driven intelligence in action, as we showcase a live demo that highlights the enhanced capabilities of WebRTC applications. Explore the technical implementation, discover industry use cases, and unlock new possibilities for immersive real-time video experiences.

Sanida Bratt Single Presenter

For decades, Wi-Fi was the go-to technology for inside the four walls and commercial cellular networks were the mainstay in outdoor environments. Private wireless networks were more of a fringe solution.While Wi-Fi works great for office spaces, homes, etc., the technology requires greater investment in “uncarpeted” enterprise environments such as factories, warehouses, shipyards, utility/energy sites, and even hospitality venues, where the business case for private wireless (4G/5G/CBRS) has strengthened.The presentation will cover why and how private wireless are more reliable for IoT use cases and how use of APIs are enabling ease of installation and cost effective deployment and ongoing operations of private wireless networks.

Warren Bent Single Presenter

The RTC Conference at Illinois Tech is passionate about fostering innovation, collaboration, and technological advancements. With a focus on demonstrating the power of programmable real-time communications, the inaugural HackRTC brought together developers, designers, and tech enthusiasts the weekend prior to the conference to create prototype solutions (hacks) utilizing developer resources provided by HackRTC Sponsors LiveKit and INdigital. In this presentation, we'll showcase some of the prize-winning demo pitches representing hacking team's solutions to real-world problems.

Federico Sciammarella Single Presenter

In today's global environment, manufacturers continue to provide more value at lower costs to their customers. Their competitive advantages come from understanding the real-time manufacturing data, making changes, and shifting as needed. This has been made possible with the proliferation of IIoT; however, to scale it technologies like 5G need to be leveraged as the number and complexity of devices increase. As the National Center for Digital Manufacturing and Cybersecurity, MxD (Manufacturing times digital) has taken on the challenge to help demystify and demonstrate how manufacturers can leverage 5G. The MxD 5G Program is a ~$5M effort administered under a cooperative agreement with the US Army Construction Engineering Research Laboratory (ARMY CERL).The MxD 5G Program is focused on advancing connectivity modernization within the manufacturing sector. This program seeks to accomplish this by establishing a methodology to investigate and test the various types of 5G cellular architecture, 5G cybersecurity, and IOT applications of 5G wireless technology to determine the appropriate configurations for use in industrial facilities. The 5G system will also serve as an ongoing testbed for industry and DoD for additional use cases in the future. The program will cover 5G System Configuration Research for Industrial Facilities to High-Speed Encryption 5G Integration Evaluation. This presentation will provide an overview of the 5G program and provide the ongoing efforts in this space.

Dana Kemack Goot Single Presenter

Music Real-time Communication applications (M-RTC) enable music making (musiking) for musicians simultaneously across geographic distance. When used for musiking, M-RTC such as Zoom and JackTrip, require satisfactorily received acoustical perception of the transmitted music to the end user; however, degradation of audio can be a deterrent to using M-RTC for the musician. Specific to the audio quality of M-RTC, we evaluate the quality of the audio, or the Quality of Experience (QoE), of five network music conferencing applications through quantitative perceptual analysis to determine if the results are commensurate with data analysis. The ITU-R BS.1534-3 MUlti Stimulus test with Hidden Reference and Anchor (MUSHRA) analysis is used to evaluate the perceived audio quality of the transmitted audio files in our study and to detect differences between the transmitted audio files and the hidden reference file. A comparison of the signal-to-noise ratio (SNR) and total harmonic distortion (THD) analysis to the MUSHRA analysis shows that the objective metrics may indicate that SNR and THD are factors in perceptual evaluation and may play a role in perceived audio quality; however, the SNR and THD scores do not directly correspond to the MUSHRA analysis and do not adequately represent the preferences of the individual listener. Since the benefits of improved M-RTC continue to be face-to-face communication, face-to-face musiking, reduction in travel costs, and depletion of travel time, further testing with statistical analysis of a larger sample size can provide the additional statistical power necessary to make conclusions to that end.

Mohan Krishna Mangamuri Single Presenter

With the integration of Big Data and speech technology, healthcare applications are poised to become more accurate, personalized, and patient-centric. Here’s how Big Data can be integrated with speech technology in healthcare: 1. Speech Recognition: Big Data can be used to train and improve speech recognition algorithms, allowing for more accurate and efficient transcription of spoken words and medical dictation. This can assist healthcare professionals in documenting patient encounters, creating medical records, and streamlining administrative tasks. 2. Clinical Documentation: By analyzing large volumes of speech data, along with other relevant patient information, Big Data can help automate clinical documentation. It is possible to extract valuable insights from speech data using Natural Language Processing (NLP) techniques, converting spoken words into structured data that is easy to analyze and integrate with electronic health records (EHRs). 3. Voice-Enabled Virtual Assistants: Voice-enabled virtual assistants, such as chatbots or smart speakers, can be developed using Big Data-powered speech technology to provide patients with personalized health information, guidance, and reminders. These virtual assistants can be integrated with medical databases and continually updated with the latest research and treatment guidelines. 4. Disease Diagnosis and Monitoring: Speech analysis techniques, combined with Big Data analytics, can help identify patterns and markers in speech that are indicative of certain diseases and conditions. For example, changes in voice pitch, tone, or rhythm can be correlated with conditions like Parkinson\\\'s disease, depression, or autism spectrum disorders. By continuously monitoring and analyzing speech data, healthcare providers can detect early signs of diseases, track disease progression, and personalize treatment plans. 5. Patient Sentiment Analysis: Big Data analytics can be applied to patient sentiment and emotional analysis and also to population health management.

Dr. Alavikunhu Panthakkan Single Presenter

Hyperspectral data plays a crucial role in various fields, including remote sensing, environmental monitoring and medical imaging. With the increasing importance of hyperspectral data, the need for secure transmission and storage has become imperative. Protecting the ownership and integrity of hyperspectral data is essential to prevent unauthorized access and ensure its reliability. This paper presents a novel approach to address these challenges by introducing a secure and efficient reversible watermarking method for ownership protection. The proposed method embeds ownership information into the hyperspectral data without affecting the spectral information. The technique involves three steps: embedding, extraction and restoration, and enables reversible watermark removal. The performance of the method is evaluated using metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Normalized Correlation (NC) and shows high ownership protection while maintaining visual quality and fidelity. The experimental results confirm the effectiveness of the proposed technique and show its robustness to various attacks and computational efficiency. This research helps preserve the integrity of hyperspectral data and provides a reliable solution for property protection in critical decision-making applications.

Chirag Chhablani Single Presenter

Digit recognition is of utmost importance in processing payment information, phone numbers, and various numerical data. Accurate and efficient digit recognition plays a crucial role in ensuring seamless user experiences and preventing errors in critical tasks. Therefore, in this project, our primary goal is to train a domain-specific Kaldi Automatic Speech Recognition (ASR) model that can recognize digits of up to five digits. Recent advancements in ASR have often focused on the power of large-scale, domain-general models. However, in very constrained domains, a domain-specific \\\"micro\\\" model may outperform general-purpose models. Micro models are a lightweight mechanism compared to a large-scale, general model. Using a general ASR model, like Whisper or Amazon Transcribe, to do digit recognition is akin to breaking open a peanut with a sledgehammer. While the results will likely be sufficient, there are more effective approaches. For this reason, we train a Kaldi model on open-source single-digit utterances and test its ability to recognize variable-length digit strings, with a maximum length of five.To achieve robust digit recognition, we also curate a dataset that not only encompasses digits of various lengths, but also contains training observations that discern numerical digits pronounced by humans in diverse manners. For instance, the number 653 may be articulated as \\\"six hundred and fifty-three,\\\" \\\"six fifty-three,\\\" or even \\\"sixty-three five.\\\" This diversity in digit lengths and pronunciation styles ensures that the model can effectively handle different numeric representations encountered in real-world scenarios. Our dataset comprises 14,000 instances collected from three diverse data sources, providing a comprehensive and representative collection of real-world numeric patterns. Through this project, we aim to contribute to the advancement of domain-specific ASR models, fostering more efficient and accurate digit recognition in critical applications.

Anne Lee Single Presenter

The IP Multimedia Subsystem (IMS) began as the Telecom industry’s vision to go All-IP and today with over 4 billion globally deployed devices, it is poised to revolutionize the phone call. Standardization of IMS began in 1999 right before the Dot Com bust. However, deployment came years later during the rise of the OTTs. IMS has gone through its ups and downs over time – somewhat reminiscent of artificial intelligence’s springs and winters – but has ultimately succeeded as the communications pie also expanded significantly. This is mainly due to the strength of its interoperability and the social contract expected with the public.Now, the combination of IMS with WebRTC – specifically the Data Channel – sets the stage for enabling limitless apps while on a voice or video call, revolutionizing and enhancing the way people communicate in C2C, B2C, B2B, and public safety scenarios. What is truly innovative about this platform is that it enables fast creation of non-standardized web apps while maintaining the important benefits of IMS standardized interoperability and at the same time making it unnecessary for users to pre-install or pre-register for the apps. In addition, only one of the CSPs in a call need to offer any particular IMS DC app in order for all parties on the call to use it. How does IMS Data Channel do this?In this talk, you will hear the details that answer this question and more. Potential new business models will also be discussed.

Deeksha Prabhakar Single Presenter

This presentation focuses on speaker separation, which aims to separate individual speakers from a mixture of voices or background noise, commonly known as the \\\"cocktail party problem.\\\" The objective is to separate the two original audios from their mix and analyze the features present that contribute to separation. The analysis proposes obtaining features from the original data and evaluating their impact on the model\\\'s ability to separate mixed audio streams.The dataset is prepared to use these feature values as predictor variables for various models such as Logistic Regression, Decision Trees, SVM, XGBoost, and AdaBoost. The goal is to identify the most contributing features that lead to better separation. The results are then analyzed to determine the features that have the most significant effect on separating the audio streams.The study begins by selecting 400 audio streams from the VoxCeleb dataset and combining them to form 200 single utterances. The pre-trained Speechbrain model, sepformer-whamr, is utilized to separate the audio mixes and obtain two outputs that closely resemble the original sources. A feature list is generated from the 400 chosen audios, and the impact of certain features on the model\\\'s capability to distinguish between multiple audio sources in a mixed recording is assessed. Permutation feature importance and SHAP values are used as analysis parameters to determine the features that have a greater effect on separation.The hypothesis of the study is that the features contributing the most to effective separation are consistent across datasets. To test this hypothesis, 1,000 audio streams are obtained from the Mozilla Common Voice Dataset, and the same experimental methodology is applied. The results demonstrate that the features extracted from the VoxCeleb dataset are indeed invariant and aid in separating the audio streams of the Mozilla Common Voice dataset.

Rajesh Sankaran Single Presenter

From the sensor to the laptop, from the telescope to the supercomputer, from the microscope to the database, scientific discovery is part of a connected digital continuum that is dynamic and fast. In this new digital continuum, artificial intelligence (AI) is providing tremendous breakthroughs, making data analysis and automated responses possible across the digital continuum. At Argonne National Laboratory and Northwestern University, we have been researching and deploying the next-generation of environmental sensing and IoT systems built by combining the powerful edge-computing paradigm with cutting-edge AI/ML algorithms and techniques. Sage is a National Science Foundation funded project to build a national cyberinfrastructure for programmable edge computing, leveraging Department of Energy (DOE) funded Waggle AI@Edge platform. This new edge computing programming framework gives scientists a new tool for exploring the impacts of global urbanization, natural disasters such as flooding and wildfires, and climate change on natural ecosystems and city infrastructure. The Sage infrastructure allows scientists to write “software-defined sensors” by analyzing the data in situ, at the edge, at the highest resolution of data. Data from the edge computation are then transmitted to a cloud computing infrastructure where they can be archived and provided to the community as data products or used in real time to trigger computational models or dynamically modify subsequent edge computation. Sage is deploying cyberinfrastructure in environmental test-beds in California, Montana, Colorado, and Kansas, in the National Ecological Observatory Network, and in urban environments in Illinois and Texas. In this talk, using Sage and other DOE efforts that utilize Waggle as examples, we will discus

David Diaz Single Presenter

WebRTC videoconferencing has risen to prominence in recent years with a sharp increase in remote work and communication. Conferences with large numbers of participants and/or high-quality video streams can overload network and CPU resources and degrade performance, limiting the use of the technology. Several partial solutions exist to mitigate these issues, such as simulcast and Scalable Video Coding (SVC), but these solutions have shortcomings and require trade-offs that make them inadequate for some scenarios. We propose Demand-Aware Adaptive Streaming, a novel method of increasing network and CPU efficiency that reduces stream quality—and thus resource consumption—at the source when possible. The method entails using WebRTC data channels to track the presented resolution of each video stream and adapting stream quality to match presentation requirements. The video publisher maintains full quality when required and adaptively reduces quality when possible. We show that the proposed method has advantages over existing methods in that it reduces network bandwidth and CPU requirements for all participants—senders and receivers—in a WebRTC videoconference.

David Turner Single Presenter

In the contemporary age of data-driven decision-making and Internet of Things (IoT), the application of real-time spatial computing in building sustainability and occupant health enhancement has gained significant traction. The field is further bolstered by the emergence of AI-enhanced platforms like SpaceBot.ai that amalgamate sensors, analytics, and dashboards into a single holistic solution.In this presentation, we explore SpaceBot.ai's innovative approach to real-time spatial computing and how it is poised to revolutionize the realm of sustainable building management and occupant well-being. SpaceBot.ai offers unparalleled 360-degree visibility and AI-enhanced analytics to derive valuable insights into environmental performance, space utilization, and behavioral patterns. This comprehensive suite aids operators in automating and prioritizing tasks, thereby streamlining space management.We delve into how SpaceBot.ai equips space planners, operators, and administrators with actionable intelligence. This capability is pivotal in driving informed, data-driven decisions that promote productivity, comfort, and satisfaction, while concurrently reducing costs and reinforcing environmental sustainability.Join us as we unpack the intricacies of this cutting-edge technology and envisage the future of smart buildings, where IoT and AI coalesce to redefine our understanding of space management.

Azeemuddin Syed Single Presenter

Voice Activity Detection (VAD) is a crucial signal processing technique employed to discern voiced and unvoiced segments within speech signals. Its significance extends to various applications such as Speech Coding, Voice Controlled Systems, and speech feature extraction. In Adaptive multi rate (AMR) speech coding, VAD plays a pivotal role in efficiently coding diverse speech frames at varying bit rates. In this presentation, we showcase the application of the Zero-Phase Zero Frequency Resonator (ZP-ZFR) as a VAD, specifically implemented on hardware.ZP-ZFR, characterized by its Infinite Impulse Response (IIR) filter nature, offers the distinct advantage of requiring a lower filter order, rendering it suitable for hardware implementation. Our proposed system\\\'s focal point is its implementation using TIMIT database, utilizing the Nexys Video Artix-7 FPGA board. The implementation journey unfolds through Vivado 2021.1, a widely recognized tool in FPGA development, with Verilog as the chosen Hardware Description Language (HDL).By presenting this research on hardware, we contribute a versatile solution that holds potential across various applications. Our presentation aims to encapsulate the essence of our work, highlighting the efficacy of ZP-ZFR in VAD and its seamless integration within hardware environments.

David vonThenen Single Presenter

Join us on a fascinating journey as we transform edge devices into interactive voice-driven personal assistants using Generative AI agents. In this session, we will explore the integration of AI-powered task management systems like BabyAGI or AutoGPT, leveraging their capabilities to create intelligent and context-aware personal assistants. Discover how these edge devices, equipped with voice recognition and synthesis, can seamlessly handle tasks, provide real-time assistance, and enhance productivity. Witness a live demonstration of this cutting-edge technology, showcasing the potential of edge devices as indispensable personal assistants. Don\\\'t miss this opportunity to dive into the world of AI-enhanced edge devices and unlock their full potential in everyday life.

Dr. Alavikunhu Panthakkan Single Presenter

The advent of the Internet of Things (IoT) has revolutionised the way devices connect to each other, but it has also brought with it significant security concerns. Intrusion detection systems (IDS) have been deployed as a countermeasure against the increasing number of cyber attacks on IoT devices. Machine learning algorithms have shown promising capabilities in detecting these attacks. In this research paper, we present a comprehensive performance analysis of different machine learning algorithms used in IoT intrusion detection systems. Specifically, we evaluate six different algorithms: Logistic Regression, K-Nearest Neighbours, Decision Tree, Random Forest, Gradient Boosting and XGBoost. Our evaluation focuses on their effectiveness in detecting fraudulent activities in the IoT domain. Several evaluation metrics such as accuracy, precision, recall, F1 score and Matthews correlation coefficient are used to assess performance. This comprehensive analysis helps improve IoT security and provides valuable insights into the efficiency of machine learning algorithms for intrusion detection. Our experimental results highlight the outstanding performance of the Random Forest model on all evaluation metrics.

James Kinney Single Presenter

INteractAI is a proof of concept product that INdigital created to prove modern LLM(s) use for Real-Time Testing and Training. This presentation will outline the key functions available and dive into the high level of how using 3rd party perspectives and the basic general intelligence baked into an LLM can create innovative solutions to solve old-school problems.

Henning Schulzrinne Single Presenter

IoT systems can control life-and-safety devices or generate highly private data. Increasingly, they are part of control loops, with environmental sensors controlling actuators, from HVAC systems to physical access. Such systems must also be flexible - nobody wants to update a C program when a new device replaces an older one. Thus, we have been exploring policy languages and tools expressing safety, privacy, and functionality constraints. Examples include: Occupancy data might only be available with a delay to prevent alerting burglars. Data analytics applications may have access to summary data, but not individual devices, to ensure privacy. Some appliances may defer running if the home solar system supplies higher-priority in-home consumers. Heating and air conditioning should not run at the same time.

Alex Gruber Single Presenter

Alex Gruber will discuss the pivotal role that AI technologies play within the call center domain. Focusing on practical applications like live audio translation and transcription, Gruber will illustrate how these tools not only eliminate language barriers but also streamline workflow, ensuring that emergency calls are directed to the most appropriate resources swiftly. He will explore the concept of call triage, where AI can analyze data to prioritize calls based on urgency, thereby assisting human agents in making informed decisions. Gruber will also delve into the concept of sentiment analysis tools, which will detect stress levels in call takers and offer insights into managing workload and emotional well-being. His talk will underscore Carbyne's commitment to leveraging AI to enhance human potential, leading to more effective, efficient, and successful Emergency Call Center operations.

Shahzil Sheikh Single Presenter

While deployment of internet of things applications has only become mainstream in the last decade or so, the ability to intelligently control devices remotely has been something that the industry has been working on for over half a century.In this talk we will review IoT communication protocols developed over the years, and some of the problems they encountered. Then we'll take a deep dive into the current state of the industry, including an outlook for modern IoT communication protocols from X10 to Matter and beyond

Adan K. Pope Single Presenter

What emergency communications centers do with IoT-driven incident data and imagery is quickly becoming more important than how those additional data are generated and transmitted. The public expects that the supplemental data that they provide will be used by first responders to render aid; first responders likewise value those data but also want the emergency communications centers to aggregate and analyze the relevant information for them. In this presentation, Intrado will address the ways in which service and solutions providers can bridge the gap between the sources of supplemental data and public safety workflows, uncertainties, and operational challenges. Topics discussed will include data brokering practices, location-centricity versus map-centricity, and innovative approaches around the Safety Internet of Things and geofencing of an emergency incident.

Andy Rollins Single Presenter

Asynchronous messaging continues to be one of the most preferred forms of communication, not only between two or more people, but between applications and people. Person to person (P2P) messaging dominates the space, whether that is using device specific messaging services (Apple iMessage and Google RCS), application specific services (WhatsApp, Facebook Messenger, SnapChat, WeChat, etc.), or standards-based traditional services like SMS and MMS. In addition, application to person (A2P) services are also growing, with natural language interactions with bots that allow people to do things like check reservations, order plane tickets, and the interactions. A2P is available in some form via all messaging services. This talk with discuss the current status of messaging in the industry, how messaging continues to expand, and the challenges that messaging continues to face.

Brandon Abley Panelist
Brooks T. Shannon, ENP Panelist
Eric Burger Panelist
Mark Fletcher Moderator

As technology advances, there always remains an elusive parameter holding back innovation. For landlines, it was the caller’s identity; and then, the caller\\\'s address. Once those issues were solved, the callers went mobile and nomadic. The industry responded with X and Y coordinates, with ever-increasing pinpoint accuracy. And with that virtually solved, the new conundrum is Z. While that can relate to the Height Above Ellipsoid (HAE), or Height Above Average Terrain, it’s a number that represents some level of altitude that must be correlated back to a specific floor. This well-versed panel of industry experts will discuss the ins and outs, as well as the ups and downs of the elusive Z element for location services.

Suresh Borkar Single Presenter

Network Slicing is a powerful capability in 5G wireless access based on the notion of logical networks customized to specific applications. It utilizes architectural entities including Cloud Based Architecture, Separation of Control and User Planes, Network Function Virtualization (NFV), and Software Defined Networking (SDN). This talk focuses on the programmability and management of Network Slices for the real time Ultra-Reliable Low Latency Communications (UR-LLC) 5G offer characterized by stringent data delivery and latency requirements. The use cases include autonomous vehicle, e-Health, and factory automation. The key entities involved in provisioning, in particular, the Generic network Slice Template (GST) and network Application Function (AF) and their usage are covered. The Network Slice information model and the relationship between GST and network slice Network Resource Management (NRM) Service Profile are highlighted. How provisioning, is enabled based on foundational and use case specific attributes, e.g., throughput, User Equipment (UE) characteristics, mobility, priority levels, security, and isolation considerations is addressed.

Dr. Biswaranjan Senapati Single Presenter

Applications for the fifth generation (5G) and beyond are growing, necessitating greater computational and complicated data processing. When compared to traditional machine learning methodologies, quantum computing and quantum learning algorithms are being used to improve processing capacity, data computation, secure communication and being capable to manage the industrial manufacturing critical business. QC can be used to increase spectrum support, improve global coverage, energy efficiency, security, performance and big-data processing. Future 6G systems will benefit from quantum information technology's (QIT) quick advancements in processing and communication.This talk explains how QIT may be used in upcoming 6G wireless networks in a technologically advanced and futuristic manner. Through real-time optimization (RTO) and machine learning, 6G wireless networks may provide immersive services like VR, AR, MR, and tactile Internet. Future wireless networks may benefit from quantum-inspired optimization methods and quantum computing assistance. In this talk, we cover the groundwork for the novel idea of quantum-inspired RTO and its implementation in 6G wireless networks' optimum resource allocation in detail.

Mark Fletcher Single Presenter

As commercial entities remediate for compliance with federal legislation, mandating direct access and dispatchable location be provided to ECCs for 911 calls from enterprise network clients, companies are deploying Additional Data Repositories to supply that critical information on MLTS 911 calls. With 80% or more of 911 calls originating from cellular devices, this critical information is not being supplied on the bulk of calls to 911. NG911 allows the originating endpoint to contribute location information that can be used to query the relevant enterprise ADR, where that valuable commercial enterprise information can also be associated with public call events. This provides Public Safety with additional disability into a location, as well as the potential for access control to be shared with responding Law-enforcement teams. This can include access to cameras, floorplans, as well as live interactive data, with the appropriate permissions being granted. This session will discuss the high-level architecture and data flow that enable this new capability with NG 911 functional elements.