Advanced real-time indoor tracking based on the Viterbi algorithm and semantic data

A real-time indoor tracking system based on the Viterbi algorithm is developed. This Viterbi principle is used in combination with semantic data to improve the accuracy, that is, the environment of the object that is being tracked and a motion model. The starting point is a fingerprinting technique for which an advanced network planner is used to automatically construct the radio map, avoiding a time consuming measurement campaign. The developed algorithm was verified with simulations and with experiments in a building-wide testbed for sensor experiments, where a median accuracy below 2 m was obtained. Compared to a reference algorithm without Viterbi or semantic data, the results indicated a significant improvement: the mean accuracy and standard deviation improved by, respectively, 26.1% and 65.3%. Thereafter a sensitivity analysis was conducted to estimate the influence of node density, grid size, memory usage, and semantic data on the performance

mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks

Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, experimental evaluation is a very time-consuming task. It depends on many factors, such as the use of the radio transceiver or the distance between nodes. Simulations reduce considerably this time. They allow the evaluation of the network behavior before its deployment. This article presents a simulation tool which helps developers to obtain information about battery state. This simulator extends the well-known TOSSIM simulator. Therefore it is possible to evaluate TinyOS applications using an accurate model of the battery consumption and its relation to the radio power transmission. Although an specific indoor scenario is used in testing of simulation, the simulator is not limited to this environment. It is possible to work in outdoor scenarios too. Experimental results validate the proposed model.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570

RSSI Based Indoor Passive Localization for Intrusion Detection and Tracking

A real time system for intrusion detection and tracking based on wireless sensor network technology is designed by using the IITH mote which is de- veloped and designed in IIT Hyderabad as the communication module in the network.This paper describes the Device-Free Passive Localization system based on RSSI.The main objective of this paper is to design a DFP Local- ization system that is easily redeployable, recon�gurable, easy to use, and operates in real time. In addition the detection of humans is to be done.The em- bedded intrusion detection algorithm is designed so that it is able to cope with the limited resources, in terms of computational power and available memory space, of the microcontroller unit (MCU) found in the nodes. and various challenges and problem faced during the real test bed deployment and also proposed solutions to overcome them.We presented an alternative algo- rithm based on the minimum Euclidean distance classi�er.our result shows that the localization accuracy of this system is increased when using the proposed algorith

UWB-assisted real-time localization in wireless sensor networks

A safety monitoring and accident warning system for underground construction site has been designed in our previous work based on wireless sensor networks (WSNs). Real-time localization of mobile targets is crucial for tracking the related incidents. However, the current RSSI-based localization approach struggles to achieve the required performance. This is due to the limited ranging accuracy of RSSI devices. In this paper, we investigate various ways of improving the localization accuracy and propose our solution of a hybrid UWB-assisted approach. We argue that a hybrid UWB-assisted RSSI ranging has the best overall performance for our application. We show with both mathematical analysis and demonstration system that, instead of implementing a full UWB network, our approach can improve the accuracy to our desired level with only a small number of additional UWB anchor nodes. © 2013 IEEE

LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN

The localization of the sensor nodes is a fundamental problem in wireless sensor networks. There are a lot of different kinds of solutions in the literature. Some of them use external devices like GPS, while others use special hardware or implicit parameters in wireless communications. In applications like wildlife localization in a natural environment, where the power available and the weight are big restrictions, the use of hungry energy devices like GPS or hardware that add extra weight like mobile directional antenna is not a good solution. Due to these reasons it would be better to use the localization’s implicit characteristics in communications, such as connectivity, number of hops or RSSI. The measurement related to these parameters are currently integrated in most radio devices. These measurement techniques are based on the beacons’ transmissions between the devices. In the current study, a novel tracking distributed method, called LIS, for localization of the sensor nodes using moving devices in a network of static nodes, which have no additional hardware requirements is proposed. The position is obtained with the combination of two algorithms; one based on a local node using a fuzzy system to obtain a partial solution and the other based on a centralized method which merges all the partial solutions. The centralized algorithm is based on the calculation of the centroid of the partial solutions. Advantages of using fuzzy system versus the classical Centroid Localization (CL) algorithm without fuzzy preprocessing are compared with an ad hoc simulator made for testing localization algorithms. With this simulator, it is demonstrated that the proposed method obtains less localization errors and better accuracy than the centroid algorithm.Junta de Andalucía P07-TIC-0247

Filtering Effect on RSSI-Based Indoor Localization Methods

Indoor positioning systems are used to locate and track objects in an indoor environment. Distance estimation is done using received signal strength indicator (RSSI) of radio frequency signals. However, RSSI is prone to noise and interference which can greatly affect the accuracy performance of the system. In this paper Internet of Things (IoT) technologies like low energy Bluetooth (BLE), WiFi, LoRaWAN and ZigBee are used to obtain indoor positioning. Adopting the existing trilateration and positioning algorithms, the Kalman, Fast Fourier Transform (FFT) and Particle filtering methods are employed to denoise the received RSSI signals to improve positioning accuracy. Experimental results show that choice of filtering method is of significance in improving the positioning accuracy. While FFT and Particle methods had no significant effect on the positioning accuracy, Kalman filter has proved to be the method of choice in for BLE, WiFi, LoRaWAN and ZigBee. Compared with unfiltered RSSI, results showed that accuracy was improved by 2% in BLE, 3% in WiFi, 22% in LoRaWAN and 17% in ZigBee technology for Kalman filtering method

Robust blimps formation using wireless sensor based on Received Signal Strength Indication (RSSI) localization method

This paper suggests the wireless communication technique used to determine the information of blimp localization (distance and orientation) via wireless sensor network (WSN) protocol. In cooperative decentralized system, information exchanges between the agents are crucial. Each agent is required to share data to enable individual decision making task. In this work, the WSN were used as the data communications protocol which provides robust communication using the mesh networking. In order to support the multi agent communication network, the reliability of data needs to be proved. The performances of the communication selection were studied through experimental and simulation approach. The experimental results showed that the RSSI value from the device provided good statically data fit using the R-square with value of 0.947. This paper also proposed a new mobile node arrangement with hexagonal anchor node arrangement based on water particles formation. The node arrangement was simulated using the Senelex™ and showed low absolute error position thus achieving the desired cooperative system requirement