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Proceedings ArticleDOI

Estimate distance measurement using NodeMCU ESP8266 based on RSSI technique

TL;DR: This work used two NodeMCU (ESP8266 WiFi module) which is a easily programmable which acts itself as a sensor node and used RSSI technique to determine the distance between two nodes.
Abstract: The use of WiFi is now a part of each human life. Airports, railways, bus-stand, home, markets everywhere now people uses WiFi because its reliability and low-cost. WiFi is also applicable in future tech of IoT (Internet of Things). In this work we used two NodeMCU (ESP8266 WiFi module) which is a easily programmable. NodeMCU which acts itself as a sensor node can be used as Access Point (AP) or as a STAtion (STA). We used one node as a AP and another as a STA. To locate a device distance measurement one of most important issue. There are lots of technique to find out the distance between two nodes (e.g. Time of Arrival (TOA), Time Difference of Arrival (TDOA) or Received Signal Strength (RSS) algorithms etc). In this work we use RSSI technique to determine the distance. First, we take around 300 sample data (RSSI values) and find the standard deviation to calculate how much the RSSI values are spread out and use curve fitting technique to find suitable equation for estimate distance. Then, we compared the estimated distance with actual distance to find the error level in percentage. We are success to reduce the average error level up to 8.32%.
Citations
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Journal ArticleDOI
TL;DR: The surveying of recent research in this area can support a better understanding of smart-city solutions based on popular platforms such as Raspberry Pi, BeagleBoard and Arduino, as presented in this article.
Abstract: With the increasing availability of affordable open-source embedded hardware platforms, the development of low-cost programmable devices for uncountable tasks has accelerated in recent years. In this sense, the large development community that is being created around popular platforms is also contributing to the construction of Internet of Things applications, which can ultimately support the maturation of the smart-cities era. Popular platforms such as Raspberry Pi, BeagleBoard and Arduino come as single-board open-source platforms that have enough computational power for different types of smart-city applications, while keeping affordable prices and encompassing many programming libraries and useful hardware extensions. As a result, smart-city solutions based on such platforms are becoming common and the surveying of recent research in this area can support a better understanding of this scenario, as presented in this article. Moreover, discussions about the continuous developments in these platforms can also indicate promising perspectives when using these boards as key elements to build smart cities.

40 citations

Journal ArticleDOI
TL;DR: This work presents the People Mobility Analytics (PmA) solution, which collects probe requests generated by Wi-Fi devices when scanning the radio channels to detect Access Points and processes the collected data to extract key insights on the people mobility.

16 citations

Journal ArticleDOI
01 Nov 2019
TL;DR: A system was proposed to reduce the level of fraud in filling the attendance list and effectiveness of student data processing using a system of applying the concept of the Internet of Things (IoT) with the fingerprint presence method.
Abstract: Lecture attendance data at universities is a reference in showing the credibility of each student used by lecturers as data for student grades as well as an evaluation material for the success of teaching and learning activities in lectures, but there are several examples of cases related to student attendance data currently prevalent in the world of education or lectures is the phenomenon of "Leave Absence" or better known as TA. In addition, other problems also arise from lecturers and administrative staff, namely difficulties in monitoring student attendance and efforts to validate attendance data because of the large amount of student data. Therefore in this study a system was proposed to reduce the level of fraud in filling the attendance list and effectiveness of student data processing using a system of applying the concept of the Internet of Things (IoT) with the fingerprint presence method. Existing system modeling results are expected to be able to support the service of processing academic data automatically and produce accurate and accurate statistical data and be able to reduce data manipulation factors from irresponsible parties.

14 citations

Journal ArticleDOI
TL;DR: This paper describes the development of a system to detect the presence of an object and monitor it, based on four NodeMcu modules programmed under Arduino IDE and communicating between them via the HTTP protocol.
Abstract: In recent years, wireless sensors networks (WSNs) have been imposed as an effective means of interconnection with simultaneous communication and information processing. They allow operating with sensors at low cost and low power consumption in various application areas such as ecosystem monitoring, detection and monitoring of objects and smart cities, etc.This paper describes the development of a system to detect the presence of an object and monitor it. This prototype is based on four NodeMcu modules (a static access point that provides the WIFI network, a server, a client and a mobile access point attached to the remote surveillance object) programmed under Arduino IDE and communicating between them via the HTTP protocol. The remote monitoring of the object for a linear disposition of the nodes used is based on the existence of the mobile access point in the HTTP client field.

10 citations

Proceedings ArticleDOI
30 Nov 2020
TL;DR: The preliminary results suggest that the proposed solution may be a viable alternative to ensure social distancing as a practice to face the pandemic caused by COVID-19.
Abstract: This paper presents the prototype of a compact and low-cost wearable electronic device that, based on the reading of the Wi-Fi signal strength emitted by other wearable devices of the same type, estimates the proximity between users and issues a notification (an audible and visual alarm) when the distance between them is less than a reference value. Our preliminary results suggest that the proposed solution may be a viable alternative to ensure social distancing as a practice to face the pandemic caused by COVID-19.

8 citations


Cites background from "Estimate distance measurement using..."

  • ...Ademais, existem inúmeros relatos sobre o uso da potência de sinais recebidos (RSSI - Received Signal Strength Indicator) para estimativa de distância [1] e localização de dispositivos [9][15]....

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  • ...[1] Suvankar Barai, Debajyoti Biswas, and Buddhadeb Sau....

    [...]

References
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Journal ArticleDOI
TL;DR: The results demonstrate that the proposed method considerably outperforms the existing algorithms in terms of positioning accuracy, which is defined as the cumulative distribution function of position error.
Abstract: Indoor localization based on Wi-Fi received signal strength indication (RSSI) has the advantage of low cost and easy implementation compared with a range of other localization approaches. However, Wi-Fi RSSI suffers from multipath interference in indoor dynamic environments, resulting in significant errors in RSSI observations. To handle this issue, a number of different methods have been proposed in the literature, including the mean method, Kalman filter algorithm, and the particle filter algorithm. It is observed that these existing methods may not perform sufficiently well in ever-changing dynamic indoor environments. This paper presents an algorithm to improve RSSI observations by using the average of a number of selected maximum RSSI observations. Smoothness index is employed to evaluate the quality of RSSI so as to select an appropriate number of RSSI observations. Experiments were conducted in four rooms and a corridor within an office building and the results demonstrate that the proposed method considerably outperforms the existing algorithms in terms of positioning accuracy, which is defined as the cumulative distribution function of position error.

176 citations

Proceedings ArticleDOI
19 Feb 2015
TL;DR: A novel multi-step approach combining Flat Earth Model, Free Space Friis Model and Linear Approximation Model for measuring distance from RSSI for smart devices with Bluetooth Low Energy (BLE) connectivity significantly achieves 13.4% reduced error of measured distance.
Abstract: Measuring distance from Received Signal Strength Indication (RSSI) of wireless devices has become one of the rudimentary but challenging requirements for Indoor Positioning and Indoor Navigation (IPIN). To address this subject, we propose a novel multi-step approach combining Flat Earth Model, Free Space Friis Model and Linear Approximation Model for measuring distance from RSSI for smart devices with Bluetooth Low Energy (BLE) connectivity. To get better result we proposed an improved averaging and smoothing algorithm of RSSI. We have significantly achieved 13.4% reduced error of measured distance.

54 citations

Proceedings ArticleDOI
23 Dec 2010
TL;DR: In this article, the authors review the current solutions and analysis models in this field, and summarize the characters of different studies, and point out some new interests and development trend of future research.
Abstract: Wireless networks based on IEEE 802.15.4 have paid great attention to the coexistence problem between themselves and with other non-IEEE 802.15.4 wireless networks. This problem has been further emphasized by two new industry wireless standards, WirelessHART and ISA100 that are set to meet special industry requirements. In this paper, we firstly review the current solutions and analysis models in this field, and summarize the characters of different studies. Then, based on the survey study, we point out some new interests and development trend of future research. Finally, we discuss about some open research issues and suggest some solutions.

53 citations


"Estimate distance measurement using..." refers background in this paper

  • ...In Wireless Sensor Network (WSN), RSSI measurements [1], [2], multipath [3] is a relevant issue for the distance measurement performance....

    [...]

Proceedings ArticleDOI
Lisheng Xu1, Feifei Yang1, Yuqi Jiang1, Lei Zhang1, Cong Feng1, Nan Bao1 
12 Sep 2011
TL;DR: This paper comprehensively analyses the characteristics of RSSI possibly influenced by the factors such as temperature, the height of sensor node's position, the type of antenna and the electromagnetic interference of human body and found that the attenuation of Received Signal Strength (RSS) varies about 5.0 dBm with the change of temperature in every 10 centigrade.
Abstract: Semiconductor manufacturers provide low-cost, low-power and short-range solutions for the application of Wireless Sensor Network (WSN), such as ZigBee, Bluetooth, Wi-Fi etc. The quality of radio frequency signal, which carries information in wireless communication channel, is the key to WSN. But it is easily influenced by the external environment. Received Signal Strength Indicator (RSSI) is a measurement for the quality of radio frequency signal which is often used in field of space localization. This paper comprehensively analyses the characteristics of RSSI possibly influenced by the factors such as temperature, the height of sensor node's position, the type of antenna and the electromagnetic interference of human body. We found that the attenuation of Received Signal Strength (RSS) varies about 5.0 dBm with the change of temperature in every 10 centigrade. The ground can reduce the radiation area of wireless signal, so that RSS is dramatically influenced by the height of its position. Patch antenna causes the attenuation of RSS about 11.2 dBm larger than helix antenna in the distance of 25 m. If the sensor node is wore in human body, the posterior position leads to the attenuation of RSS about 13.0∼16.2 dBm larger than anterior position in a specified distance range due to the electromagnetic interference of human body. Finally, some improvement devices were raised here for the WSN in the application of home healthcare according to the qualified effects of various environmental factors.

33 citations

Proceedings ArticleDOI
01 Oct 2007
TL;DR: Results from an empirical investigation are presented as to the attainable accuracy of a Radio Frequency (RF) positioning system based on received signal strength (RSS).
Abstract: Implementing positioning systems for indoor environments is notoriously difficult. The vast array of interacting parameters such as furniture, room shape and materials mean that the simulation of such an environment is of limited value. We present in this paper results from an empirical investigation as to the attainable accuracy of a Radio Frequency (RF) positioning system based on received signal strength (RSS). Methods to improve confidence, such as frequency averaging and bi-directional ranging, are explored. Finally we present and evaluate a novel method for calibrating the channel propagation exponent with no prior knowledge of the sensor network layout or room shape.

25 citations


"Estimate distance measurement using..." refers methods in this paper

  • ...There are several methods proposed in [4], [5], [6], [7], [8] to the RSSI measurements....

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