Indoor Location Systems based on ZigBee networks (original) (raw)
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JURNAL INFOTEL
Wireless network technology that is used today is developing rapidly because of the increasing need for location information of an object with high accuracy. Global Positioning System (GPS) is a technology to estimate the current location. Unfortunately, GPS has a disadvantage of low accuracy of 10 meters when used indoors. Therefore, it began to be developed with the concept of an indoor positioning system. This is a technology used to estimate the location of objects in a building by utilizing WSN (Wireless Sensor Network). The purpose of this study is to estimate the location of the unknown nodes in the lecturer room as an object and obtain the accuracy of the system being tested. The positioning process is based on the received signal strength (RSSI) on the unknown node using the ZigBee module. The trilateration method is used to estimate unknown node located at the observation area based on the signal strength received at the time of testing. The result shows that the path loss...
Woc, 2006
To verify the validity of our previously reported autonomous indoor localization system in an actual environment, we implemented it in a wireless sensor network based on the ZigBee standard. The system automatically estimates the distance between sensor nodes by measuring the RSSI (received signal strength indicator) at an appropriate number of sensor nodes. Through experiments, we clarified the validity of our data collection and position estimation techniques. The results show that when the deployment density of sensor nodes was set to 0.27 nodes/Ñ ¾ , the position estimation error was reduced to 1.5-2 m.
Indoor Position System Based on a Zigbee Network
Communications in Computer and Information Science, 2013
TAIS group has developed an indoor position system prototype based on a fingerprint positioning algorithm. The prototype uses IEEE 802.15.4 mote and BitCloud Stack, a full-featured ZigBee Compliant, second generation embedded software stack from Atmel. The design requirements of the prototype were only to determine the actual position in a room of a user in a building, so the prototype accuracy is room accuracy. TAIS group decided to compete in the second edition of EvAAL Competition. This paper presents all the step made to adapt the prototype to the EvAAL environment, the found drawbacks and the obtained results. One of the most important drawback was that the Smart House Living Lab of the Polytechnic University of Madrid has only two rooms, the required accuracy was meters (error less than or equal to 0,5 meters the higher score, higher than 4 meters no score) and the room accuracy was substituted by areas of interest so the behavior of our prototype was going to work was an incognita.
Research on the ZigBee-Based Indoor Location Estimation Technology
Communications in Computer and Information Science, 2011
In recent years, as rapid advances in wireless and mobile communications and continuing decreases in hardware costs, applications of the wireless sensor network are widespread; whereas location estimations in the wireless sensor technology are crucial for their use. Among them, Location-based services have been developed rapidly and find their applications in areas such as medical care, warehouse management, and mobile guide systems in public spaces. In this paper, a fingerprint based location estimation technology in the ZigBee networks is investigated, in which the collection method to build the signal strength database and the configuration of sensor nodes are examined. Furthermore, the k-nearest neighbor algorithm is used to increase accuracy of location estimations for compliance with relevant applications.
Indoor Localization of a Mobile Object via Zigbee-Based RSSI
International Journal of Electrical and Electronic Engineering & Telecommunications
Being able to accurately track a moving object has been one of the main challenges in smart building applications. In this paper, an indoor localization technique for a mobile object using Zigbee-based Received Signal Strength Indication (RSSI) is considered. In order to alleviate the multipath effects from surrounding, a method utilizing the smoothness index to select RSSI values with best quality is proposed. The proposed strategy is evaluated via a simple experiment where the object with a receiver antenna is placed on a wheeled mobile robot moving on a predefined trajectory at a constant speed. The result is also compared with other standard filtering approaches, and the performance is analysed in terms of position error at each time instance between the initial and final positions of the object. Experimental results show that the cumulative error can be significantly reduced as compared to the results from other standard approaches.
This thesis report describes a model for monitoring the presence and movements of vehicles and humans in an indoor environment. In IEEE 802.15.4 the Received Signal Strength Indicator is used to determine the quality of the communication from one node to another. By tagging vehicles/humans with a ZigBee node and deploy a number of nodes at fixed position in the room, the received signal strength indicator can be used to determine the position of tagged object. This system operates by recording and processing signal strength information at multiple base stations positioned to provide information in the area of interest. It combines Euclidean distance technique with signal strength matrix obtained during offline measurement to determine the location of user. The experimental results presented in this report demonstrate the ability of this system to estimate user's location with a high degree of accuracy.
Journal of Robotics and Control (JRC), 2020
Wireless sensor networks (WSNs) have a vital role in indoor localization development. As today, there are more demands in location-based service (LBS), mainly indoor environments, which put the researches on indoor localization massive attention. As the global-positioning-system (GPS) is unreliable indoor, some methods in WSNs-based indoor localization have been developed. Path loss model-based can be useful for providing the power-distance relationship the distance-based indoor localization. Received signal strength indicator (RSSI) has been commonly utilized and proven to be a reliable yet straightforward metric in the distance-based method. We face issues related to the complexity of indoor localization to be deployed in a real situation. Hence, it motivates us to propose a simple yet having acceptable accuracy results. In this research, we applied the standard distance-based methods, which are is trilateration and min-max or bounding box algorithm. We used the RSSI values as the localization parameter from the ZigBee standard. We utilized the general path loss model to estimate the traveling distance between the transmitter (TX) and receiver (RX) based on the RSSI values. We conducted measurements in a simple indoor lobby environment to validate the performance of our proposed localization system. The results show that the min-max algorithm performs better accuracy compared to the trilateration, which yields an error distance of up to 3m. By these results, we conclude that the distance-based method using ZigBee standard working on 2.4 GHz center frequency can be reliable in the range of 1-3m. This small range is affected by the existence of interference objects (IOs) lead to signal multipath, causing the unreliability of RSSI values. These results can be the first step for building the indoor localization system, which low-cost, lowcomplexity, and can be applied in many fields, especially indoor robots and small devices in internet-of-things (IoT) world's today.
RSSI-Based Indoor Localization and Identification for ZigBee Wireless Sensor Networks in Smart Homes
IEEE Transactions on Instrumentation and Measurement, 2018
Location-based services have increased in popularity in recent years and can be fruitfully exploited in the field of smart homes, opening the doors to a wide range of personalized services. In this context, radio technology can be widely employed since, other than connecting devices in the home system, it offers solutions for the user localization issue without the need of any extra device. Techniques based on received signal strength indicator (RSSI) are often used, relying on fingerprinting or proximity algorithms. In this paper, a novel RSSI-based fingerprinting approach for room-level localization is presented: it is a threshold algorithm based on receiver operating characteristic analysis. Moreover, the actual user location is estimated from his/her interaction with the home system devices deployed in the house: if the home environment is inhabited by more than one person, it becomes of utmost importance the identification of who is actually interacting with a given device. A proximity method is exploited for this purpose. Tests have been carried out to characterize the approach, particularly, the effects of RSSI samples, number and position, of the anchor nodes have been analyzed. Finally, some considerations about power consumption of the mobile node have been presented.
Accurate Indoor Localization for ZigBee Networks
2018 3rd International Conference on Computer Science and Engineering (UBMK), 2018
Localization has critical role for location-based services in wireless sensor networks (WSN). Various techniques have been proposed but accurate indoor localization is still an active research area. In this paper, we performed experimental studies on data collection and compared position prediction techniques for indoor environments. Findings of this study indicate that time of arrival based prediction gives better results than receiver signal strength indicator (RSSI) based prediction. Keywords-Internet of things, indoor positioning, indoor tracking, wireless sensor networks.