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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/introduction-to-internet-of-things
课程评论：没有评论
课程名称：《物联网入门》 概述：注册参加由孟买印度理工学院（IIT Bombay）与TIH物联网与物联网（IoT & IoE）基金会联合开设的《物联网入门》课程。本课程包括四个模块，为学习者提供了在物联网动态领域中所需的基础知识和技能。 学习目标：该课程由Rajbabu Velmurugan教授、Laxmeesha Somappa教授和Gaurav S. Kasbekar教授领导，旨在帮助学习者理解物联网的基本概念。 课程大纲： 1. **物联网（IoT）：入门** - 由Rajbabu Velmurugan教授主讲，课程深入探讨物联网的基本概念、应用及其独特特征。第一课讲解物联网的本质，第二课介绍物联网的各种模型及组件，并通过家庭自动化等实例进行说明。最后一课分析物联网架构及设计目标，为希望掌握物联网基础知识的学习者提供了必要的入门知识。 2. **传感器与接口** - 由Laxmeesha Somappa教授主讲，这一模块深入探讨传感器的特性及其接口技术。第一课介绍传感器的分类，并通过具体案例研究不同类型的传感器。第二课讲解传感器的关键特性如灵敏度、准确性和响应时间，随后课程关注传感器读数处理，介绍模数转换（ADC）及其设计选择，最后探讨可能遇到的非理想问题。 3. **物联网节点的网络** - 由Gaurav S. Kasbekar教授主讲，本模块深入连接各类物联网节点的机制和挑战，以确保无缝通信与数据交换。第一课介绍物联网节点的概念及其在农业、医疗、智能家居和基础设施等领域的应用，分析网络中的挑战。第二课探讨低功耗、低数据率网络，介绍IEEE 802.15.4标准及LoRa与SigFox等前沿技术。第三课聚焦于受限设备的集成，介绍6LoWPAN、头压缩、分片及路由协议，最后一课涵盖IoT所需的消息传递协议，全面介绍CoAP与MQTT的格式及其通信细节。 4. **物联网的数据分析** - 由Rajbabu Velmurugan教授主讲，该模块关注分析物联网设备生成的大量数据。第一课探讨数据分析对于物联网的重要性，介绍适用于IoT数据集的学习方法及其可行性，结合Python的实践操作。第二课深入特定的数据分析技术，包括线性回归、时间序列模型及聚类方法。通过理论与实践结合的内容，帮助学习者掌握在物联网领域中利用数据分析的能力，并以TIH-IoT首席执行官的特别寄语作为结尾，为学习者提供了丰富的实用经验和视野。 本课程致力于为学习者打下坚实的理论基础，提供实践见解，确保他们在物联网的网络环境中游刃有余。
Name:Internet of Things (IoT): An Introduction
Description:Led by Prof. Rajbabu Velmurugan, in the "Internet of Things (IoT): An Introduction" module, learners will embark on a comprehensive journey into the fundamentals of IoT. Lesson 1 delves into the very essence of IoT, exploring its applications and distinct characteristics. Progressing to Lesson 2, participants will uncover the diverse models and components of IoT, enriched with real-world examples like home automation. Concluding with Lesson 3, the module offers an in-depth analysis of IoT architecture and its design goals, ensuring a holistic understanding of the subject. With a well-curated blend of videos and insights, this module serves as an essential primer for anyone keen on grasping the basics of the IoT realm.
Name:Sensors & Interfaces
Description:Led by Prof. Laxmeesha Somappa, the "Sensors & Interfaces" module offers a comprehensive exploration into the intricate world of sensors, their characteristics, and their interfacing techniques. Lesson 1 serves as a foundational introduction to the realm of sensors, delving into their classifications and providing in-depth case studies on select sensor types like accelerometers, displacement/proximity sensors, and temperature sensors. Building on this foundation, Lesson 2 dives into the vital characteristics that define and differentiate sensors, covering aspects such as sensitivity, accuracy, and response time. The subsequent lessons shift focus to the crucial process of sensor readout, with Lesson 3 elucidating the concepts and design choices surrounding Analog to Digital Conversion (ADC) and quantization, and Lesson 4 highlighting the non-idealities one might encounter, including opamp specific issues.
Name:Networking of IoT Nodes
Description:Led by Prof. Gaurav S. Kasbekar, the "Networking of IoT Nodes" module delves deep into the mechanisms and challenges of connecting diverse IoT nodes, ensuring seamless communication and data exchange. Lesson 1 lays the foundation by introducing the concept of IoT nodes, their diverse applications in sectors like agriculture, healthcare, smart homes, and infrastructure, and outlines the challenges in their networking. Lesson 2 ventures into low power, low data rate networks, illuminating participants on the IEEE 802.15.4 standard, as well as cutting-edge technologies like LoRa and SigFox. In Lesson 3, the spotlight is on the integration of constrained devices, offering insights into 6LoWPAN, header compression, fragmentation, and routing protocols. Rounding off the module, Lesson 4 dives into messaging protocols essential for IoT, with a comprehensive overview of CoAP and MQTT, their formats, and communication intricacies.
Name:Data Analysis for IoT
Description:Led by Prof. Rajbabu Velmurugan, in the "Data Analysis for IoT" module, learners delve into the critical aspects of analyzing vast amounts of data generated by IoT devices. Beginning with an exploration of the significance of data analysis specifically for IoT in Lesson 1, participants will be introduced to the components, feasibility, and various types of learning methods tailored for IoT datasets, with hands-on Python-based implementations. Lesson 2 offers a deeper dive into specific data analysis techniques, encompassing linear regression, time-series models, and clustering methodologies. With a blend of theoretical insights and practical demonstrations, this module ensures that learners are well-equipped to harness the power of data in the IoT domain. Concluding with a special message from the CEO of TIH-IoT. This module is a blend of theoretical knowledge, practical insights, and real-world applications, ensuring learners are well-equipped to navigate the networking landscape of IoT.
Enroll in "Introduction to Internet of Things," a meticulously curated course by the eminent faculty of IIT Bombay in conjunction with TIH Foundation for IoT & IoE. This comprehensive course, spanning four modules, equips learners with foundational knowledge and skills essential to navigate the dynamic landscape of IoT. The Learning Objectives of this four-module course led by Prof. Rajbabu Velmurugan, Prof. Laxmeesha Somappa and Prof. Gaurav S. Kasbekar include - - Understand the fundamental
