scholarly journals Sistem Monitoring Kadar Gas Metana (Ch4), Gas Amonia (Nh3) Dan Gas Karbon Dioksida (Co2) Pada Tempat Pembuangan Sampah Untuk Pencegahan Penyakit Ispa Berbasis Wireless Sensor Network

2021 ◽  
Vol 11 (4) ◽  
pp. 220-227
Author(s):  
Lova Nugroho ◽  
Rachmad Saptono ◽  
Aad Hariyadi
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Packet Loss ◽  
Peer To Peer ◽  
Wireless Sensor ◽  
Line Of Sight

Adanya teknologi Wireless Sensor Network (WSN) dimanfaatkan untuk membuat sistem sistem monitoring kadar gas pada tempat pembuangan akhir sampah, khususnya tiga gas yang akan dimonitoring yaitu gas metana (CH4), gas amonia (NH3) dan gas karbondioksida (CO2) yang dapat mengakibatkan penyakit infeksi saluran pernafasan. Sistem monitoring ini memanfaatkan teknologi Wireless Sensor Network supaya dapat memonitoring daerah yang lebih luas dengan menggunakan jumlah node yang banyak. Hasil komunikasi menggunakan modul nRF24L01 dari node sensor ke server dengan model komunikasi peer to peer dalam kondisi Line of Sight dapat berkomunikasi pada jarak maksimal 120meter dengan rata – rata delay yaitu 6.98s dan packet loss saat pengiriman data sebanyak 14% yang termasuk kategori buruk menurut ITU-T G.114. Kemudian untuk mengetahui kualitas jaringan saat melakukan pengiriman data dari server ke firebase dengan software wireshark didapatkan delay 261ms, kemudian untuk packet loss didapatkan nilai 8.3% masuk ke dalam kategori baik menurut ITU-T G.114.

scholarly journals A Non-Parametric Propagation Condition Identification Method and Non-Line of Sight Mitigation Algorithm for Wireless Sensor Network

2016 ◽  
Vol 10 (1) ◽  
pp. 80-87 ◽  
Author(s):  
Hao Chu ◽  
Cheng-dong Wu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Propagation Condition ◽  
Localization Accuracy ◽  
Chi Squared ◽  
Potential Applications ◽  
Unknown Node ◽  
Non Line Of Sight

The wireless sensor network (WSN) has received increasing attention since it has many potential applications such as the internet of things and smart city. The localization technology is critical for the application of the WSN. The obstacles induce the larger non-line of sight (NLOS) error and it may decrease the localization accuracy. In this paper, we mainly investigate the non-line of sight localization problem for WSN. Firstly, the Pearson's chi-squared testing is employed to identify the propagation condition. Secondly, the particle swarm optimization based localization method is proposed to estimate the position of unknown node. Finally the simulation experiments are implemented. The simulation results show that the proposed method owns higher localization accuracy when compared with other two methods.

scholarly journals Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771772269 ◽  
Author(s):  
Alejandro Cama-Pinto ◽  
Gabriel Piñeres-Espitia ◽  
José Caicedo-Ortiz ◽  
Elkin Ramírez-Cerpa ◽  
Leonardo Betancur-Agudelo ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Packet Loss ◽  
Precision Agriculture ◽  
Signal Intensity ◽  
Path Loss ◽  
Field Tests ◽  
Wireless Sensor ◽  
Intensity Level ◽  
Log Normal

Today, through the monitoring of agronomic variables, the wireless sensor networks are playing an increasingly important role in precision agriculture. Among the emerging technologies used to develop prototypes related to wireless sensor network, we find the Arduino platform and XBee radio modules from the DIGI Company. In this article, based on field tests, we conducted a comparative analysis of received strength signal intensity levels, calculation of path loss with “log-normal shadowing” and free-space path loss models. In addition, we measure packet loss for different transmission, distances and environments with respect to an “Arduino Mega” board, and radio modules XBee PRO S1 and XBee Pro S2. The tests for the packet loss and received strength signal intensity level show the best performance for the XBee Pro S2 in the indoor, outdoor, and rural scenarios.

scholarly journals A Hierarchical Voting Based Mixed Filter Localization Method for Wireless Sensor Network in Mixed LOS/NLOS Environments

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2348 ◽  
Author(s):  
Yan Wang ◽  
Jinquan Hang ◽  
Long Cheng ◽  
Chen Li ◽  
Xin Song
Keyword(s):  
Kalman Filter ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Unscented Kalman Filter ◽  
Rapid Development ◽  
Mobile Node ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Localization Method

In recent years, the rapid development of microelectronics, wireless communications, and electro-mechanical systems has occurred. The wireless sensor network (WSN) has been widely used in many applications. The localization of a mobile node is one of the key technologies for WSN. Among the factors that would affect the accuracy of mobile localization, non-line of sight (NLOS) propagation caused by a complicated environment plays a vital role. In this paper, we present a hierarchical voting based mixed filter (HVMF) localization method for a mobile node in a mixed line of sight (LOS) and NLOS environment. We firstly propose a condition detection and distance correction algorithm based on hierarchical voting. Then, a mixed square root unscented Kalman filter (SRUKF) and a particle filter (PF) are used to filter the larger measurement error. Finally, the filtered results are subjected to convex optimization and the maximum likelihood estimation to estimate the position of the mobile node. The proposed method does not require prior information about the statistical properties of the NLOS errors and operates in a 2D scenario. It can be applied to time of arrival (TOA), time difference of arrival (TDOA), received signal (RSS), and other measurement methods. The simulation results show that the HVMF algorithm can efficiently reduce the effect of NLOS errors and can achieve higher localization accuracy than the Kalman filter and PF. The proposed algorithm is robust to the NLOS errors.

scholarly journals Secure and Distributed On-Demand Randomized Routing in WSN

2016 ◽  
Vol 15 (6) ◽  
pp. 6850-6856
Author(s):  
V. Upendran ◽  
R. Dhanapal
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Packet Loss ◽  
Distributed Algorithm ◽  
Wireless Sensor ◽  
Network Dynamic ◽  
On Demand ◽  
Dynamic Route ◽  
Candidate Node

Security and energy efficiency is of paramount importance in a wireless sensor network. This is due to their vulnerabledeployment conditions and battery based power. This paper presents a secure and distributed algorithm that generatesroutes on-demand in a wireless sensor network. Dynamic route generation is facilitated by PSO, a metaheuristictechnique. Current network traffic in that route and charge contained in the candidate node are used as evaluationparameters along with the node distance, hence a huge reduction in the packet loss was observed. Experiments wereconducted and it was observed that the proposed algorithm exhibits very low selection overhead and also providesdistributed routs, which eventually lead to prolonged network lifetime.

scholarly journals Comparative Analysis of TCP, SCTP and MPTCP in Transport Layer of Wireless Sensor Networks

10.29007/h7cg ◽  
2018 ◽  
Author(s):  
Geerija Lavania ◽  
Preeti Sharma ◽  
Richa Upadhyay
Keyword(s):  
Comparative Analysis ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Packet Loss ◽  
Data Transfer ◽  
Reliable Data ◽  
Transport Layer ◽  
Wireless Sensor ◽  
Destination Node ◽  
Reliable Data Transfer

The wireless sensor network is the network that has large number of sensor nodes that are connected to each other. The wireless nodes sense the event and forward packets to the destination node. A transport layer handles congestion and packet loss recovery for reliable data transfer in WSN. There exist several protocols at the transport layer in WSN for reliable data transfer like ESRT, ATP, Tiny TCP/IP, PORT, CTCP, RTMC, DCDD, RETP etc. Each protocol has its merits and demerits. Traditional network uses TCP and UDP protocol at the transport layer. In WSN, these are not suitable. In this work, the TCP, SCTP and MPTCP are compared in the wireless sensor network environment. The wireless network with packet loss is considered. From the comparative analysis, we get the result that MPTCP gives the better performance than TCP and SCTP in the wireless sensor network.

scholarly journals A Robust Tracking Algorithm Based on a Probability Data Association for a Wireless Sensor Network

2019 ◽  
Vol 10 (1) ◽  
pp. 6
Author(s):  
Long Cheng ◽  
Mingkun Xue ◽  
Ze Liu ◽  
Yong Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Association ◽  
Position Estimation ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Network Technology ◽  
Probabilistic Data ◽  
Probabilistic Data Association ◽  
Non Line Of Sight

As one of the core technologies of the Internet of Things, wireless sensor network technology is widely used in indoor localization systems. Considering that sensors can be deployed to non-line-of-sight (NLOS) environments to collect information, wireless sensor network technology is used to locate positions in complex NLOS environments to meet the growing positioning needs of people. In this paper, we propose a novel time of arrival (TOA)-based localization scheme. We regard the line-of-sight (LOS) environment and non-line-of-sight environment in wireless positioning as a Markov process with two interactive models. In the NLOS model, we propose a modified probabilistic data association (MPDA) algorithm to reduce the NLOS errors in position estimation. After the NLOS recognition, if the number of correct positions is zero continuously, it will lead to inaccurate localization. In this paper, the NLOS tracer method is proposed to solve this problem to improve the robustness of the probabilistic data association algorithm. The simulation and experimental results show that the proposed algorithm can mitigate the influence of NLOS errors and achieve a higher localization accuracy when compared with the existing methods.

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