To support your role in inspiring students to pursue careers in STEM-related fields, we are pleased to offer the following program which provides a complete STEM curriculum for grade 11-12 students. This program will provide access to STEM content and the technical expertise of our IEEE members to help you integrate this content into your teaching practice. The program will be delivered from January to June 2025. [] The program begins with a guided 16-week presentation of a (https://www.cool-mcu.com/bundles/rpi-pico-robotics-and-iot-curriculum-for-pre-university-educators), followed by regularly scheduled office hours as you apply the concepts into your teaching practice. Please review the following video which describes the program: https://youtu.be/LBHYEj2qobs This training is targeted towards Grade 11/12 Computer or Electronics Engineering Teachers, and will be delivered virtually using a Learning Management System, combined with weekly live Q/A sessions to verify mastery of the material. When registering, please complete all address fields, so we can ship you a robot kit and track in time for the kick-off session! Agenda: Kick-Off Meeting Agenda: Outcomes Courses & Topic Coverage IoT Robot Hardware Review Using the LMS Detailed Training Schedule Assigned reading and lab exercise Virtual: https://events.vtools.ieee.org/m/436135

[] In this presentation, we will first explore the vision for 6G networks as envisioned by standardization bodies and industry leaders. We will then delve into two key aspects of 6G: AI integration and immersive communication. To illustrate our research in these areas, we will present two case studies: (1) edge intelligence-empowered integrated sensing and communication, and (2) user-centric mobile augmented reality. Speaker(s): Professor Jie Gao, Agenda: 12:00pm - 12:30pm: Talk by Professor Jie Gao 12:30pm - 12:45pm: Networking and Lunch 12:45pm - 1:00pm: Remainder of Talk with Q/A Room: RBCx Finance Quarter, Bldg: Hub350, 350 Legget Dr, Ottawa, Ontario, Canada, K2K 3N1

IEEE Toronto Section is pleased to announce a DL day, which brings together distinguished lecturers from the IEEE Communications Society (ComSoc), Signal Processing Society (SPS), and Vehicular Technology Society (VTS) in a single event. This offers attendees an unparalleled opportunity to engage with renowned professionals who are at the forefront of innovation in their respective fields.​ The event will feature cutting-edge talks on topics such as multilayer networks, self-supervised Wi-Fi sensing, semantic communications with diffusion models, digital twin networks for vehicle platoons, pervasive intelligence in 6G systems, and emerging cybersecurity threats with current state-of-the-art defenses.​ Join us for a day filled with insightful talks, engaging discussions, and valuable networking opportunities. Whether you're a graduate student, young researcher, or industry professional, this event offers new perspectives on the latest advancements in the field. Please complete a FREE registration before May 25 at vTools to reserve your lunch and coffee/refreshments. Room: ENG-LG02, Bldg: George Vari Engineering and Computing Centre, Toronto Metropolitan University, 245 Church Street, Toronto , Ontario, Canada

Robotic odor source localization is a technology that enables a mobile robot or autonomous agent to locate hidden odor sources in unknown environments. This approach has significant potential for replacing human searchers in hazardous situations, such as detecting chemical leaks or gas emissions. The key challenge lies in designing effective navigation algorithms that allow the robot to respond appropriately to sensory inputs. This presentation explores various olfactory-based navigation strategies, including AI-driven algorithms and semantic navigation approaches that fuse visual and olfactory data. The presentation also highlights real-world applications that demonstrate the capabilities and impact of robotic odor source localization systems. [] Virtual: https://events.vtools.ieee.org/m/486172

Robotic odor source localization is a technology that enables a mobile robot or autonomous agent to locate hidden odor sources in unknown environments. This approach has significant potential for replacing human searchers in hazardous situations, such as detecting chemical leaks or gas emissions. The key challenge lies in designing effective navigation algorithms that allow the robot to respond appropriately to sensory inputs. This presentation explores various olfactory-based navigation strategies, including AI-driven algorithms and semantic navigation approaches that fuse visual and olfactory data. The presentation also highlights real-world applications that demonstrate the capabilities and impact of robotic odor source localization systems. [] Virtual: https://events.vtools.ieee.org/m/486172

Please join us for an upcoming lecture on 2 June 2025 at 3 – 4 pm (Eastern Time) by Dr. Benoit Derat, Senior Director for Systems Developments and Project Implementations, at Rohde & Schwarz, Munich, Germany. Date: Monday, 2 June 2025 Time: 3:00 PM to 4:00 PM (EST) Location: Room BA 2135, Bahen Centre for Information Technology, 40 St George St, Toronto How Close Can Far-Field Be? Getting the Best Out of Your Measurement Range Trends in modern wireless communications, including the use of massive MIMO and millimeter wave frequencies, have supported an increased deployment of electrically large antennas. This created technical and economic challenges as many EMC or regulatory tests require a far-field condition. This talk provides an overview of the recent findings in defining the shortest possible far-field test distance, depending on the size of the device under test, its operation frequency, the target metric and the upper bound acceptable measurement deviation. Practical ways are also described to determine the maximum antenna aperture size that can be tested in the far-field at a given frequency and for a maximum error, in an existing chamber with a defined range length. Speaker(s): Benoit Derat Room: BA 2135, Bldg: Bahen Centre for Information Technology, 40 St George Street, Toronto, Ontario, Canada, M5S 2E4

To support a wide range of vertical applications with limited resources, future connected systems rely on highly efficient distributed collaboration. However, with the growing complexity of tasks and resources as well as the dynamic evolution of network topologies, efficiently selecting appropriate capabilities and resources within connected systems to ensure effective task completion is becoming a significant challenge. To address this, we propose using trust as the unified evaluation framework to enable task-oriented resource and capability selection, and present detailed strategies on how trust evaluation can facilitate effective task completion in various types of connected systems. First, a rapid trust evaluation mechanism is introduced for highly dynamic Internet of Vehicles systems to enable timely and efficient collaborator selection. Additionally, task-specific accurate trust evaluation is explored through the use of Generative AI and machine learning techniques to facilitate effective task completion. Moreover, a trusted multi-task and multi-collaborator matching framework is developed using hypergraphs to uncover device dependencies under specific tasks. Furthermore, a spatio-temporal trust evaluation method is proposed for multi-hop collaboration, leveraging Large Language Model (LLM)-enabled agents to facilitate privacy-preserving collaborator selection. Finally, several open challenges are discussed to highlight future research directions. Virtual: https://events.vtools.ieee.org/m/487171

Trends in modern wireless communications, including the use of massive MIMO and millimeter wave frequencies, have supported an increased deployment of electrically large antennas. This created technical and economic challenges as many EMC or regulatory tests require a far-field condition. This talk provides an overview of the recent findings in defining the shortest possible far-field test distance, depending on the size of the device under test, its operation frequency, the target metric and the upper bound acceptable measurement deviation. Practical ways are also described to determine the maximum antenna aperture size that can be tested in the far-field at a given frequency and for a maximum error, in an existing chamber with a defined range length. Speaker(s): Dr. Benoit Derat, Bldg: HUB 350, 350 Legget Dr., Kanata, Ontario, Canada

Abstract : Active Alignment for Photonics Assembly is a key technology in high-precision manufacturing. It ensures sub-micron accuracy by continuously optimizing component positioning in real time. Unlike passive alignment methods, Active Alignment uses live optical feedback to achieve the highest possible performance. The technology is essential for applications that demand exceptional optical precision, including Camera modules & LiDAR systems, Laser beam shaping & external cavity resonators, Optical fibers & photonic integrated circuits (PICs), and Medical imaging & high-performance optics. This tutorial talk will provide an overview of Active Alignment for Photonics Assembly, key features and applications of the technology, and an opportunity for discussion with the presenter. Co-sponsored by: McGill Optica Student Chapter. Optech. Speaker(s): Sebastian Haag Agenda: 2:00 - 2:30 pm: free networking (on-site only) 2:30 – 4:00 pm: technical seminar presentation (hybrid) Room: MC603, 6th floor, Bldg: McConnell Engineering building, 3480 rue University, Montreal, Quebec, Canada, H3A 0C3, Virtual: https://events.vtools.ieee.org/m/487104

IEEE North Saskatchewan Section Meeting 57 Campus Dr, Saskatoon, Saskatchewan, Canada, S7N 5A9, Virtual: https://events.vtools.ieee.org/m/469122