An applied Swiss-inspired curriculum combining algorithmic rigour, systems architecture, digital trust and practical engineering capability for modern technology leaders.
The MSc in IoT and Connected Systems at Brookfield School of Computing is engineered to provide deep competency across core computer science, systems design, and targeted domain applications. Students develop fluency in software craftsmanship, distributed architectures, algorithm optimization, and data governance.
Instruction balances rigorous theoretical foundations with practical code repositories, laboratory simulations, and ethical technology review aligned with modern international computing standards.
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| IOT711 | Advanced Kinematics, Dynamics & Non-Linear Control Systems in IoT and Connected Systems | Theory | Derive forward/inverse kinematics, Newton-Euler equations, Lie groups SE(3) and Lyapunov non-linear stability proofs. |
| IOT712 | Robot Operating System 2 (ROS 2) Architecture & C++ Lab | Practical | Develop modular ROS 2 nodes, lifecycle nodes, custom action servers and DDS QoS configurations in C++. |
| IOT713 | Perception, Multi-Sensor Fusion & State Estimation in IoT and Connected Systems | Theory | Formulate Extended Kalman Filters (EKF), Unscented Kalman Filters (UKF) and particle filters for multi-sensor odometry. |
| IOT714 | Sensor Calibration, IMU & LiDAR Odometry Lab | Practical | Calibrate extrinsic camera-LiDAR transforms and implement point-cloud registration using ICP and NDT algorithms. |
| IOT715 | Spatial Mathematics, Lie Algebra & Motion Representation | Theory | Formulate SO(3) and SE(3) manifolds, screw theory, exponential coordinates and quaternion representations. |
| IOT716 | Embedded Real-Time Computing & Microcontroller Lab (RTOS) | Practical | Implement low-latency motor control loops and CAN bus communication using FreeRTOS on STM32 microcontrollers. |
| IOT717 | Empirical Robotics Research Methodologies & Experimental Rigor | Theory | Design repeatable physical experiments, ground-truth motion capture tracking and statistical performance metrics. |
| IOT718 | Physics Simulation & Digital Twin Engineering (Gazebo / Isaac Sim) | Practical | Construct high-fidelity URDF models, contact dynamics and sensor noise profiles in NVIDIA Isaac Sim. |
| IOT719 | Robotics Safety Standards, ISO 10218/15066 & Swiss Machinery Law | Theory | Evaluate collaborative robot safety standards, functional safety (SIL/PL) and Swiss machinery safety regulations. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| IOT721 | Simultaneous Localization and Mapping (SLAM) & Spatial AI | Theory | Deconstruct graph-based SLAM, factor graphs, loop closure optimization (g2o/GTSAM) and visual SLAM pipelines. |
| IOT722 | Visual SLAM & LiDAR SLAM Implementation Lab | Practical | Implement real-time visual-inertial odometry (VIO) and 3D LiDAR mapping using GTSAM and Open3D. |
| IOT723 | Motion Planning, Trajectory Optimization & Optimal Control | Theory | Derive RRT*, PRM, Model Predictive Control (MPC) and differential dynamic programming (DDP) for trajectory generation. |
| IOT724 | Model Predictive Control (MPC) & Trajectory Planning Workshop | Practical | Implement non-linear MPC trajectory optimization for obstacle avoidance using CasADi and OSQP in C++. |
| IOT725 | Deep Reinforcement Learning for Robotic Manipulation & Locomotion | Theory | Evaluate actor-critic architectures (SAC, PPO), domain randomization and sim-to-real transfer for robotic control. |
| IOT726 | Sim-to-Real Reinforcement Learning Workshop | Practical | Train policy networks in GPU physics simulators and transfer weights to physical robot manipulators. |
| IOT727 | Multi-Agent Robotics, Swarm Systems & Distributed Coordination | Theory | Model consensus algorithms, decentralized task allocation and collision avoidance (ORCA/VO) in multi-robot teams. |
| IOT728 | Robotic Manipulation, Grasp Synthesis & Tactile Sensing Studio | Practical | Implement 6-DOF grasp synthesis using neural grasp planners and tactile sensor feedback on multi-fingered grippers. |
| IOT729 | Enterprise Robotics Case Study & Collaborative System Design | Practical | Deliver an autonomous robotic system design solving an industrial automation, logistics or inspection challenge in IoT and Connected Systems. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| IOT731 | Frontiers in Human-Robot Interaction (HRI) & Cognitive Robotics | Theory | Critically assess social robotics, intent recognition, shared autonomy and cognitive architectures in IoT and Connected Systems. |
| IOT732 | HRI & Shared Autonomy Interface Engineering Lab | Practical | Build teleoperation interfaces with force-feedback haptics, gesture recognition and eye-tracking attention cues. |
| IOT733 | Strategic Robotics Leadership, Industrial Automation & ROI Analysis | Theory | Formulate enterprise robotics deployment roadmaps, total cost of ownership (TCO) and industrial workplace safety. |
| IOT734 | Edge AI Acceleration & Embedded Vision Studio (Jetson / FPGA) | Practical | Optimize neural perception models for embedded NVIDIA Jetson platforms using TensorRT and DeepStream. |
| IOT735 | Cybersecurity in Robotics, Secure Teleoperation & Fleet Management | Theory | Analyze DDS security plugins, encrypted robot-to-cloud communication and firmware tampering defenses. |
| IOT736 | MSc IoT and Connected Systems Thesis Proposal Colloquium & Defense | Practical | Author and defend a formal scientific master's research proposal specifying physical and simulated robotics testbeds. |
| IOT737 | Robotics Commercialization, Venture Creation & Hardware Patents | Theory | Examine hardware startup development cycles, patent strategies, supply chain sourcing and venture fundraising. |
| IOT738 | Pre-Thesis Robotic System Prototyping & Pilot Lab | Practical | Construct initial experimental robotic subsystems or control algorithms and gather preliminary validation metrics. |
| IOT739 | Industry Fieldwork & Real-World Autonomous System Testing | Practical | Deploy and test autonomous robotic prototypes within unstructured real-world indoor or outdoor environments. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| IOT741 | MSc IoT and Connected Systems Dissertation: Empirical Methodology & Testbed Instrumentation | Practical | Establish the experimental robotics workspace, tracking calibration and benchmark test suites in IoT and Connected Systems. |
| IOT742 | MSc IoT and Connected Systems Dissertation: Autonomous Hardware-Software Integration | Practical | Engineer the complete robotic system, perception pipeline or control algorithm embodying the novel research in IoT and Connected Systems. |
| IOT743 | MSc IoT and Connected Systems Dissertation: Physical Benchmarking & Statistical Evaluation | Practical | Execute exhaustive physical/simulated trajectory trials, precision benchmarks and statistical evaluations. |
| IOT744 | Critical Literature Synthesis & State-of-the-Art Analysis in IoT and Connected Systems | Theory | Synthesize academic publications from IEEE ICRA, IROS, RSS and IJRR robotics conferences. |
| IOT745 | Scalability Benchmarking, Failure Mode & Effects Analysis (FMEA) | Practical | Subject the robotic system to edge-case stress testing, safety boundary audits and physical robustness tests. |
| IOT746 | Scientific Manuscript Preparation & Peer Review in IoT and Connected Systems | Theory | Author a publication-ready academic manuscript adhering to IEEE/ACM robotics conference conventions. |
| IOT747 | Executive Strategic Direction & Industrial Automation Advisory | Theory | Translate specialized robotics research into actionable corporate technology roadmaps and automation strategies. |
| IOT748 | Comprehensive Robotics Portfolio & Reproducible Testbed Package | Practical | Package reproducible simulation models, ROS 2 packages, CAD designs and technical documentation in IoT and Connected Systems. |
| IOT749 | MSc IoT and Connected Systems Thesis Oral Defense & Public Demonstration Viva | Practical | Conduct a live autonomous demonstration and defend the scientific master's thesis before an academic committee. |
Recognized Bachelor Degree in computing, engineering, mathematics, quantitative discipline or relevant technical equivalence. English proficiency IELTS 6.5+ or equivalent.
Brookfield School of Computing is an independent private education institution in formation. Academic programmes, entry requirements, fees and awards are subject to institutional review and applicable Swiss legal regulations.