Course information

Sensor and Data Fusion Training Course Outline

Module 1: Introduction to Data Fusion

  • What is Data Fusion?
  • Data Fusion Application
  • Advantages of Data Fusion

Module 2: Multiple Sensor System Applications and Design Considerations

  • Selection of Sensors
  • Fog Characterisation
  • Operating Frequency Effect on MMW Sensor Performance
  • Absorption and Backscatter of MMW
  • Visibility Metrics

Module 3: Data Fusion Algorithms and Architectures

  • Processing Levels
  • Data Fusion Processor Functions
  • Introduction to Architecture
  • Data Fusion Architectures

Module 4: Classical Inference

  • Estimating Population Statistics
  • Interpreting Confidence Interval
  • Significance Test for Hypotheses
  • Z-Test and T-Test for Population Mean

Module 5: Bayesian Inference

  • Overview
  • Bayes’ Rule
  • Applying Bayesian Inference to Fusion Information from Multiple Sources
  • Combine Multiple Sensor Information
  • Recursive Bayesian Updating
  • Posterior Calculation

Module 6: Dempster-Shafer Evidential Theory

  • Process Overview
  • Method Implementation
  • Dempster’s Rule for the Combination of Multiple Sensor Data
  • Dempster Shafer vs Bayesian Decision

Module 7: Artificial Neural Networks

  • Applying Artificial Neural Networks
  • Linear and Nonlinear Classifiers
  • Supervised and Unsupervised Learning
  • Supervised Learning Rules

Module 8: Voting Logic Fusion

  • Sensor Target Reports
  • Sensor Detection Space
  • System Detection Probability
  • Hardware Implementation of Voting Logic Sensor Fusion

Module 9: Fuzzy Logic and Fuzzy Neural Networks

  • Fuzzy System Elements
  • Fuzzy Logic Processing
  • Fuzzy Centroid Calculation
  • Balance Inverted Pendulum with Fuzzy Logic Control
  • Applying Fuzzy Logic to Multitarget Tracking
  • Fuzzy Neural Networks

Module 10: Passive Data Association Techniques

  • Data Fusion Options
  • Received Signal Fusion
  • Angle Data Fusion
  • Decentralised Fusion Architecture

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Who should attend this Sensor and Data Fusion Training Course?

The Sensor and Data Fusion Course is a comprehensive course designed to equip delegates with the knowledge and skills needed to understand and implement sensor fusion techniques for integrating and interpreting data from multiple sources. The course is useful for the following professionals:

  • Data Scientists
  • Researchers
  • Autonomous Vehicle Developers
  • Robotics Experts
  • Internet of Things Professionals
  • Environmental Monitoring Experts
  • Aerospace and Aviation Professionals

Prerequisites of the Sensor and Data Fusion Training Course

There are no formal prerequisites for the Sensor and Data Fusion Course. However, a basic understanding of sensors and reading sensor data can be beneficial.

Sensor and Data Fusion Training Course Overview

This Sensor and Data Fusion Course is designed to equip delegates with the knowledge of sensor fusion and sensor fusion application scenario limiting sensor size. Delegates will learn about the effects of operating wavelength on IR sensor performance. In addition, delegates will gain knowledge of how to estimate the statistics of the population.

Professionals in fields such as aerospace, defence, and autonomous systems must master Sensor and Data Fusion to optimise information processing and achieve more accurate and reliable results. This course helps delegates understand topics like linear and non-linear classifiers in detail.

This 1-day training by the Knowledge Academy equips delegates with the skills to effectively integrate data from diverse sensors, enhancing their ability to make informed decisions in complex scenarios. Delegates will gain practical insights into sensor fusion techniques, enabling them to apply these methods in their respective industries.

Course Objectives

  • To understand the principles and concepts of Sensor and Data Fusion
  • To explore various sensor technologies and their integration methods
  • To analyse real-world applications and case studies of successful sensor fusion
  • To gain hands-on experience in implementing sensor fusion techniques
  • To evaluate challenges and solutions in the field of sensor integration
  • To apply acquired knowledge to enhance decision-making processes in specific industries

Upon completion, delegates will possess a comprehensive skill set in Sensor and Data Fusion, enabling them to improve the efficiency and accuracy of decision-making in their professional roles, ultimately contributing to the success of their organisations.

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What’s included in this Sensor and Data Fusion Training Course

  • World-class Training Sessions from Experienced Instructors
  • Sensor and Data Fusion Training Certificate
  • Digital Delegate Pack

Why choose us

Our Winnipeg venue

Includes..

Free Wi-Fi

To make sure you’re always connected we offer completely free and easy to access wi-fi.

Air conditioned

To keep you comfortable during your course we offer a fully air conditioned environment.

Full IT support

IT support is on hand to sort out any unforseen issues that may arise.

Video equipment

This location has full video conferencing equipment.

­­­­Winnipeg, a city in the Canadian province of Manitoba, has an average population of roughly 663,600 spread across 179.18 square miles of land.  At The Knowledge Academy, we offer 50,000 classroom based training courses throughout the different areas of Winnipeg, in order to enhance people’s learning in an array of subject areas.  Education in Canada is generally funded by federal, provincial, and local governments; the system is divided into primary, secondary and post-secondary education and is operated under provincial jurisdiction.  On the whole, there are 190 days in a school year, starting in September and ending towards the last Friday of June.  Some popular and highly regarded universities in Canada include: the University of Toronto (notable alumni including: William Lyon Mackenzie King, Vincent Massey, Donald Sutherland and Lesra Martin), the University of British Columbia (notable alumni including: Eddie Peng, Justin Trudeau and Nardwuar the Human Serviette), and the University of Alberta (notable alumni including: Dayo Wong, George Stanley and Beverley McLachlin). 

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Address

201 Portage Avenue
18th Floor
Winnipeg
Manitoba
R3B 3K6

T: +1 6474932992

Ways to take this course

Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led Sensor And Data Fusion Training in Winnipeg. Engage directly with expert instructors, mirroring the classroom schedule for a comprehensive learning journey. Enjoy the convenience of virtual learning without compromising on the quality of interaction.

Unlock your potential with The Knowledge Academy's Sensor And Data Fusion Training in Winnipeg, accessible anytime, anywhere on any device. Enjoy 90 days of online course access, extendable upon request, and benefit from the support of our expert trainers. Elevate your skills at your own pace with our Online Self-paced sessions.

Streamline large-scale training requirements with The Knowledge Academy's In-house/Onsite at your business premises. Experience expert-led classroom learning from the comfort of your workplace and engage professional development.

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Sensor And Data Fusion Training in Winnipeg FAQs

Sensor processing and data fusion combine data from multiple sensors to create a unified, accurate view of an environment. This approach enhances decision-making by integrating diverse data types, improving reliability, and providing more precise insights in complex settings.
Data fusion refers to integrating data from multiple sources to give more consistent, accurate, and comprehensive information. It combines diverse data types to enhance analysis, improve decision-making, and support complex problem-solving across various fields.
The three levels of data fusion are Level 1 (Object Refinement), which focuses on identifying and tracking individual objects; Level 2 (Situation Refinement), which assesses the relationships and context between objects; and Level 3 (Threat Refinement), which anticipates future actions and potential risks.
Sensor fusion merges data from various sensors to improve accuracy and reliability, while data fusion combines information from multiple sources beyond sensors to provide a more comprehensive view. Both enhance decision-making but vary in scope.
Sensor-level fusion is the process of combining raw data from multiple sensors to create a more accurate and comprehensive representation of an environment. By merging this data, it improves system performance in tasks like object detection, tracking, and decision-making.
The three primary requirements for nuclear fusion are high temperature, sufficient pressure, and confinement time. High temperature is necessary to overcome electrostatic repulsion between nuclei, pressure is needed to keep particles close, and confinement time ensures particles collide to sustain fusion.
Data integration involves merging data from different sources to create a unified view, enabling easier access and analysis. Data fusion, however, goes a step further by merging this information to generate new insights, enhancing decision-making with a cohesive, enriched dataset.
There are no formal prerequisites for the Sensor and Data Fusion Course. However, a basic understanding of sensors and reading sensor data can be beneficial.
These online courses are ideal for professionals seeking to enhance their skills in specific fields, including those working in technology, management, or compliance. They are also suitable for individuals preparing for career advancements or seeking industry-recognised certifications.
Yes, The Knowledge Academy offers 24/7 support via phone & email before attending, during, and after the course. Our customer support team is available to assist and promptly resolve any issues you may encounter.
In this training course, delegates will have intensive training with our experienced instructors, a digital delegate pack consisting of important notes related to this course, and a certificate after course completion, ensuring you gain practical experience and in-depth knowledge.
This course takes 1-day to complete during which delegates participate in intensive learning sessions that cover various course topics.
The Sensor and Data Fusion Certification aims to equip professionals with the skills to integrate and analyse data from multiple sensors. It enhances their ability to improve decision-making processes, increase system accuracy, and optimise performance in various applications and industries.
This Sensor and Data Fusion Training equips delegates with essential skills to integrate data from various sources, enhancing decision-making processes. It improves analytical capabilities, supports advanced technologies, and fosters innovation in robotics, autonomous systems, and intelligent data analysis.
Holding this certification signifies expertise in integrating and interpreting data from various sensors. This knowledge enhances decision-making capabilities, supports advanced analytics, and is crucial for roles in sectors such as defence, robotics, and intelligent technology development.
The course is designed to be accessible to all levels, making it suitable for both beginners and experienced professionals. It covers foundational concepts while offering in-depth insights into personal and organisational growth strategies.
The Sensor and Data Fusion Training course would benefit individuals in roles such as data analysts, engineers, scientists, and IT professionals. This training is ideal for those involved in data integration, analytics, and developing smart systems across various industries.
In this training course, delegates will have intensive training with our experienced instructors, a digital delegate pack consisting of important notes related to this course, and a certificate after course completion.
The Sensor and Data Fusion Training course enhances your understanding of integrating data from various sources. This knowledge is crucial for developing advanced robotics, autonomous vehicles, and IoT systems, thereby improving your career prospects in cutting-edge technological fields.
In these courses and training, delegates will learn the principles of sensor technologies, data fusion techniques, and their applications. The course covers algorithms for combining data from multiple sources to enhance decision-making and improve system performance.
After completing the Sensor and Data Fusion Course, you should apply your knowledge in real-world projects, seek further certifications, engage in networking opportunities within the industry, and explore advanced courses to deepen your understanding of data fusion techniques and applications.
The Knowledge Academy provides flexible self-paced training for this course. Self-paced training is beneficial for individuals who have an independent learning style and wish to study at their own pace and convenience.
If you are unable to access your courses, contact the support team at The Knowledge Academy via their customer service email or phone number provided on their website for prompt assistance and resolution of your issue.
Upon completing the Sensor and Data Fusion course, you can expect job opportunities as a data analyst, sensor fusion engineer, robotics engineer, or systems integration specialist. These roles involve utilising data fusion techniques to enhance decision-making in various industries.
No, there is no formal exam at the end of this course. However, delegates are assessed through practical exercises and activities throughout the training to ensure they understand and can apply the concepts effectively.
The training fees for Sensor and Data Fusion Trainingin Winnipeg starts from CAD3395
The Knowledge Academy is the Leading global training provider for Sensor and Data Fusion Training.
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"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"

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