RPL attacks framework for simulating WSN with a malicious mote based on Contiki
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Updated
Jul 11, 2024 - Python
RPL attacks framework for simulating WSN with a malicious mote based on Contiki
Dense Wireless Connectivity Datasets for the IoT.
Simple Wireless-Sensor-Network Optimization using Genetic-Algorithm.
Indoor localization and pattern recognition using Numenta's HTM framework with ROS
Python-based project to show the working of a blockchain-based WSN and perform certain attacks on it to check the security.
Wormhole detection in wireless sensor networks using spanning trees.
This is a Software-Defined Wireless Sensor Network (SDWSN) controller. This SDWSN-controller is designed to work with Contiki-NG-SDWSN.
a project to optimize the number, placement, and transmit power of sensor nodes in a wireless sensor network using evolutionary algorithms and Python.
Implementing LEACH protocol in a WSN using Python, aiming to increase energy efficiency, reduce system delay, energy consumption, packet loss.
This repo provides source code for optimizing sensor sampling locations in wireless sensor networks using spatiotemporal autoencoder.
Implemented an evolutionary algorithm to optimize the cost and service quality of a city-wide communication network by adjusting the number, location, and transmit power of sensor nodes.
A. Gazis, K. Stamatis, E. Katsiri, “A Method for Counting, Tracking and Monitoring of Visitors with RFID sensors Model of Study M. Hatzidakis residence”, Panhellenic Electrical and Computer Engineering Students Conference (ECESCON), ECESCON Proceedings, Xanthi, Greece, vol.10, pp.199-204, doi: 10.5281/zenodo.3549417, March, 2018
Wireless Sensor Networks implementation for the WSN Class of 8th Semester at ECE, AUTH.
To control the flow of a wireless sensor network a supervisory algorithm for the network was developed. This project was developed in 2015 by the technological initiation program of the Pontifical Catholic University of Campinas
A repository for our undergraduate thesis that deals with the evaluation of LZMA, LZW, LEC, bzip2, and gzip with the objective of creating sustainable WSN deployments. The hardware setup is composed of workstations and Raspberry Pis with XBee RF modules. The simulations are coded in Python.
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