Lesson 1 - Trends in IoT

Introduces the Internet of Things (IoT) and its applications in the real world. It discusses the different types of IoT devices, the technologies that power IoT, and the challenges that engineers face when designing and testing IoT devices.

Lesson 2 - Convolutional Neural Networks

The use of convolutional neural networks (CNNs) in IoT applications. CNNs are a type of machine learning algorithm that can be used to identify objects and patterns in images and videos. This makes them well-suited for applications such as object detection and classification in IoT devices.

Lesson 3 - Location Finding Algorithms

The challenges of location-finding in IoT devices and how engineers are improving the accuracy and efficiency of location-finding algorithms. Location-finding is important for a variety of IoT applications, such as asset tracking, navigation, and smart city applications.

Lesson 4 - Deep Brain Stimulation Treatments

The use of deep brain stimulation (DBS) to treat people with brain disorders. DBS is a minimally invasive surgical procedure that involves implanting electrodes in the brain. The electrodes are then connected to a device that delivers electrical stimulation to specific areas of the brain. This stimulation can help to improve symptoms of a variety of brain disorders, such as Parkinson's disease, epilepsy, and depression.

Lesson 5 - Conclusions on IoT in the Real World

Discusses other real-world IoT applications, such as smart homes, smart cities, and industrial automation. Smart homes use IoT devices to control and monitor home appliances and systems. Smart cities use IoT devices to collect and analyze data about traffic, energy usage, and other city services. Industrial automation uses IoT devices to control and monitor industrial equipment.