Accelerometer Sensor Network For Reliable Pothole Detection

Author(s):  
Teodor Kalushkov ◽  
Georgi Shipkovenski ◽  
Emiliyan Petkov ◽  
Rositsa Radoeva
2010 ◽  
Vol 29-32 ◽  
pp. 233-239
Author(s):  
Guo Hua Hui

Children heart rate monitoring plays an important role among human health research field. In this paper, a synchronized intelligent sensor network was designed for children heart rate monitoring. The ECG sensor, MMA7261QT accelerometer sensor and CSR BC4 Bluetooth module were accepted for heart rate monitoring. The experimental data features were extracted by the bistable stochastic resonance data processing method. The signal-to-noise ratio (SNR) maximum value was used to judge the children action state. The experimental results showed that the designed system provided an effective method for a big scale children health monitoring.


2020 ◽  
Vol 10 (19) ◽  
pp. 6992
Author(s):  
Giva Andriana Mutiara ◽  
Nanna Suryana Herman ◽  
Othman Mohd

Nowadays, the need for wireless sensing applications is increasing. Along with the increased illegal cutting of logs in the forest, however, it requires the integration application to tackle the illegal logging and forest preservation. The wireless sensor network is a suitable network architecture for remotely monitoring or tracking applications in the environment. This paper proposed an integrated system that can identify and track the position of a moving cutting log. An Arduino Uno, Raspberry Pi 3 B+, sound sensor, accelerometer sensor, LoRa GPS HAT Shield, and Outdoor LoRa Gateway OLG01 performed the hardware monitoring and tracking of the proposed system. The network of STAR topology configuration between master and slaves is represented by the LoRa Network embedded with the sensors, as an architecture of the wireless sensor network. The system was examined the performance of the network and the tracking process. The result determined that the LoRa can detect and identify the occurrence of the illegal cutting of logs in real-time. Meanwhile, in terms of the tracking performance, a duration of 5–46 s was required to track the new position of the moving cutting log.


Author(s):  
A Mochamad Rifki Ulil ◽  
Fiannurdin ◽  
Sritrusta Sukaridhoto ◽  
Anang Tjahjono ◽  
Dwi Kurnia Basuki

Author(s):  
Shin Ishiguro ◽  
Yoshihiro Kawagishi ◽  
Ho Yihsin ◽  
Eri Sato-Shimokawara ◽  
Toru Yamaguchi

2020 ◽  
Vol 26 (11-12) ◽  
pp. 941-951 ◽  
Author(s):  
Sa’ed Alajlouni ◽  
Pablo Tarazaga

An underfloor accelerometer sensor network can be used to track occupants in an indoor environment using measurements of floor vibration induced by occupant footsteps. To achieve occupant tracking, each footstep impact location must first be estimated. This paper proposes a new energy-based algorithm for footstep impact localization. Compared to existing energy-based algorithms, the new algorithm achieves higher localization accuracy and removes a previously required calibration step (removal of the need to estimate floor-dependent parameters). Furthermore, the algorithm uses a much smaller data sampling rate compared to time of flight/arrival localization methods, which greatly reduces data and data-processing time. The new algorithm is a two-step location estimator: the first step is a coarse location estimate, with the second step as a fine location search through a nonlinear minimization problem. The performance of the proposed algorithm is evaluated using a single occupant walking experiment on an instrumented floor inside an operational smart building. This paper also demonstrates that higher localization accuracy is obtained using an additional Kalman filtering scheme.


Sign in / Sign up

Export Citation Format

Share Document