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  HOME CS3491 Syllabus - Artificial Intelligence And Machine Learning - 2021 Regulation Anna University CS3491 ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING  LTPC 3024 COURSE OBJECTIVES: • The main objectives of this course are to: • Study about uninformed and Heuristic search techniques. • Learn techniques for reasoning under uncertainty • Introduce Machine Learning and supervised learning algorithms • Study about ensembling and unsupervised learning algorithms • Learn the basics of deep learning using neural networks UNIT I PROBLEM SOLVING 9 Introduction to AI - AI Applications - Problem solving agents – search algorithms – uninformed search strategies – Heuristic search strategies – Local search and optimization problems – adversarial search – constraint satisfaction problems (CSP) UNIT II PROBABILISTIC REASONING 9 Acting under uncertainty – Bayesian inference – naïve bayes models. Probabilistic reasoning – Bayesian networks – exact inference in BN – approximate inference in BN – cau

HOME                             UNIT - 1 Architecture of IOT  In simple terms, it is a process that consists of at least 4 stages or layers, which must work along to build the IoT architecture. So, the  architecture IoT  requires connected hardware (that gathers data), a mean of communication to transmit the data to or from a cloud, a system that allows to process all data, and a data center (which can work in the cloud or in a local server) that will allow to store, handle, and analyze the information provided. Types of layers of IoT architecture   Basic layers of IoT architecture The most common layers of Internet of Things architecture are 4, however, it doesn’t mean that every IoT device has the same amount, the minimum to guarantee a stable project is four layers, but depending on the complexity, an  IoT product development company  can decide to add more layers to the project. 1. Sensing layer: This layer of IoT architecture contains all the different devices and sensors that ar

 HOME                      UNIT - 1 Introduction to IOT : We can begin to understand the Internet of Things (IoT) by imagining a future in which all of our electrical appliances—from our cars to our refrigerators, air conditioners, and light bulbs—are networked, tracked, and, on occasion, capable of acting and communicating with one another, with or without ourThis is the Internet of Things (IoT) universe. Over the last several decades, billions of people have gained access to the internet, first via desktop computers and then via smartphones and other mobile devices. Things can also benefit from this revolution in communication, not only people. M2M communication is quickly approaching its reality, despite much anticipation. More than 1.1 billion smartphones (excluding feature phones) will be in use globally in 2013, according to Parks Associates. However, this is just scratching the surface. Figure: Potential IOT Economic Impact by 2025 Source:https://www.researchgate.net/figure/Pote

HOME                 UNIT - 1 IoT Enabling Technologies Different technologies together enable development of IoT applications. The IoT enabling technologies are:   ●       Wireless Sensor Networks ●       Cloud Computing ●       BigData Analytics ●       Communication Protocols ●       Embedded Systems IoT Enabling Technologies: Wireless Sensor Networks A Wireless Sensor Network (WSN) is a collection of devices which communicate through wireless channels. A WSN consists of distributed devices with sensors which are used to monitor the environmental and physical conditions. A WSN consists of a number of end nodes, routers and coordinators. End nodes can also act as routers. A coordinator collects data from all the nodes and is connected to Internet user. Examples of WSNs used in IoT systems:   ●       Weather monitoring systems ●       Indoor air quality monitoring systems ●       Soil moisture monitoring systems ●       Surveillance systems ●       Smart gr