Big data analysis and Internet of Things(IoT)

This presentation is based on the basic of IOT and Cloud computing and their application . This presentation will give a brief idea about this field .

Here's how big data and the Internet of Things work together: a vast network of sensors (IoT) collect a boatload of information (big data) that is then used to improve services and products in various industries, which in turn generate revenue.

What IoT Is ? IoT Applications IoT Architecture IoT Protocol Development Board IoT Cloud Platform IoT prediction IoT Challanges

PPT discusses Iot, its uses and applications. The draft IoT policy by DeitY, Govt. of India is also briefly discussed.

Artificial intelligence and IoT talk at IoTBE - The Belgian Internet of Things user group November 21, 2013 iMinds

The document defines the Internet of Things as connecting physical objects through embedded technology and sensors to communicate over the Internet. It allows objects to be monitored and controlled remotely without human involvement. RFID tags are commonly used to give objects an Internet connection. The Internet of Things has applications in smart homes, cities, healthcare, transportation and more. While it provides advantages like energy savings, there are also disadvantages like privacy breaches and job losses if systems are over-relied on.

Big data is high-volume, high-velocity, and high-variety data that is difficult to process using traditional data management tools. It is characterized by 3Vs: volume of data is growing exponentially, velocity as data streams in real-time, and variety as data comes from many different sources and formats. The document discusses big data analytics techniques to gain insights from large and complex datasets and provides examples of big data sources and applications.

Internet of Things(IoT) is the latest technology making its presence felt in the world. There are various research areas for IoT thesis for M.Tech and Ph.D. Find out the latest topics for thesis and research here.

This document discusses edge and fog computing use cases from an industrial perspective. It provides examples of applications that require low latency such as autonomous vehicles, industrial automation, and healthcare. Pushing large amounts of video and sensor data to distant cloud servers is not feasible for these applications due to bandwidth limitations and latency constraints. The document then presents two example use cases where edge/fog computing solutions were implemented: 1) A smart surveillance system for an industrial township using edge devices to run video analytics locally instead of sending all video to the cloud. 2) Using edge devices to optimize operations of steam boilers by collecting sensor data, making decisions, and performing actions locally to reduce latency. Overall, the document argues that edge and fog computing are necessary