TinyOS Course 04: Sensing
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This document outlines a TinyOS programming course lesson on sensing. The lesson introduces using sensors in wireless sensor networks and provides exercises for students to retrieve sensor data from nodes, parse the data using a Netbeans project, and optionally combine radio interfaces to parse messages from other nodes as well as build a multi-hop application. Students are encouraged to work through the exercises step-by-step using provided code from previous lessons on serial communication and radio interfaces.
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I am talking all about deep learning in which we can talk about introduction ,Benefits ,
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Submit_the_SlideShare_Assignment_for_Thesis_Presentation
This document proposes using machine learning and neural networks to develop educational software to help students improve their calculating skills. It describes developing a neural network model trained on student performance data to estimate individual weak points in calculation. An experiment tests different neural network parameters and finds hidden neurons of 9 and 2000 learning iterations provides good accuracy over 99% with reasonable processing time. The proposed software would use the neural network to analyze student errors and provide personalized practice problems and explanations to target their weak areas.
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Providing security in wireless sensor networks is
a very crucial task. Because of its dynamic nature (no fixed
topology) and resource constraint devices. Which has limited
computational abilities, memory storage and physical
restrictions. Advancement in the field of intrusion and
evaesdroping has increased challenges for a secure
communication between nodes. So, establishments of pair wise
keys in a wireless network becomes a vital issue. Hence,
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fundamental challenge for providing seamless transmission
and security services. Having little resources in our hand,
it is always a tough task to design and implement protocols.
But this paper proposes a new robust key pre-distribution
scheme which resolves this issue without compromising
security. This paper presents a new mechanism to achieve
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algebraic, exponential, logarithm functions and prime
numbers. The resilience method under this scheme is based
on discontinuous functions which is hard to be spoofed.
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TinyOS Course 04: Sensing
- 1. WSN Programming Course TinyOS Lab: Lesson 04: Sensing Manuel Fernández UAH, 18th September 2013
- 2. • Introduction to sensing • Exercises 2 Contents
- 3. We have not yet used the sensors! And that is the important feature ofWSN, the ability to capture real data from the environment. 3 Sensing
- 5. 5 Header
- 6. 6 Module • Specification: • Implementation: Let’s look at Lesson04 and go step by step!
- 7. 1. Merge code from Lesson 02 (Serial Communication) and retrieve data from the sensors. Use the provided Netbeans project to parse the data. 2. If you feel brave, combine the radio interface from Lesson 03 and parse also messages from other nodes. Note: Find out how to discriminate node ids. 3. Lets try and build our own multi hop application! 7 Exercises