scholarly journals Compressed sensing with continuous parametric reconstruction

2021 ◽  
Vol 11 (1) ◽  
pp. 851
Author(s):  
Imrich Andras ◽  
Linus Michaeli ◽  
Jan Saliga
Keyword(s):  
Signal Reconstruction ◽  
Sampling Rate ◽  
Quality Monitoring ◽  
Wireless Sensor ◽  
Model Parameters ◽  
Sampling Process ◽  
Continuous Approach ◽  
Continuous Models ◽  
Stable Performance ◽  
Unconventional Method

This work presents a novel unconventional method of signal reconstruction after compressive sensing. Instead of usual matrices, continuous models are used to describe both the sampling process and acquired signal. Reconstruction is performed by finding suitable values of model parameters in order to obtain the most probable fit. A continuous approach allows more precise modelling of physical sampling circuitry and signal reconstruction at arbitrary sampling rate. Application of this method is demonstrated using a wireless sensor network used for freshwater quality monitoring. Results show that the proposed method is more robust and offers stable performance when the samples are noisy or otherwise distorted.

Sampling-rate restrictions for exponential signal reconstruction

1972 ◽  
Vol 60 (6) ◽  
pp. 726-726 ◽  
Author(s):  
F.W. Fairman ◽  
R.D. Gupta
Keyword(s):  
Signal Reconstruction ◽  
Sampling Rate

scholarly journals A novel air quality monitoring and improvement system based on wireless sensor and actuator networks using LoRa communication

2021 ◽  
Vol 7 ◽  
pp. e711
Author(s):  
Truong Van Truong ◽  
Anand Nayyar ◽  
Mehedi Masud
Keyword(s):  
Air Quality ◽  
Loss Rate ◽  
Sensor Nodes ◽  
Quality Monitoring ◽  
Full Duplex ◽  
Wireless Sensor ◽  
Air Quality Monitoring ◽  
Relay Nodes ◽  
System Information ◽  
Online Software

In this paper, we study the air quality monitoring and improvement system based on wireless sensor and actuator network using LoRa communication. The proposed system is divided into two parts, indoor cluster and outdoor cluster, managed by a Dragino LoRa gateway. Each indoor sensor node can receive information about the temperature, humidity, air quality, dust concentration in the air and transmit them to the gateway. The outdoor sensor nodes have the same functionality, add the ability to use solar power, and are waterproof. The full-duplex relay LoRa modules which are embedded FreeRTOS are arranged to forward information from the nodes they manage to the gateway via uplink LoRa. The gateway collects and processes all of the system information and makes decisions to control the actuator to improve the air quality through the downlink LoRa. We build data management and analysis online software based on The Things Network and TagoIO platform. The system can operate with a coverage of 8.5 km, where optimal distances are established between sensor nodes and relay nodes and between relay nodes and gateways at 4.5 km and 4 km, respectively. Experimental results observed that the packet loss rate in real-time is less than 0.1% prove the effectiveness of the proposed system.

scholarly journals Output Information Based Fault-Tolerant Iterative Learning Control for Dual-Rate Sampling Process with Disturbances and Output Delay

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Hongfeng Tao ◽  
Yan Liu ◽  
Huizhong Yang
Keyword(s):  
Iterative Learning Control ◽  
Fault Tolerant ◽  
Sampling Rate ◽  
Sufficient Conditions ◽  
Learning Control ◽  
Iterative Learning ◽  
Repetitive Process ◽  
Sampling Process ◽  
Output Delay ◽  
Output Information

For a class of single-input single-output (SISO) dual-rate sampling processes with disturbances and output delay, this paper presents a robust fault-tolerant iterative learning control algorithm based on output information. Firstly, the dual-rate sampling process with output delay is transformed into discrete system in state-space model form with slow sampling rate without time delay by using lifting technology; then output information based fault-tolerant iterative learning control scheme is designed and the control process is turned into an equivalent two-dimensional (2D) repetitive process. Moreover, based on the repetitive process stability theory, the sufficient conditions for the stability of system and the design method of robust controller are given in terms of linear matrix inequalities (LMIs) technique. Finally, the flow control simulations of two flow tanks in series demonstrate the feasibility and effectiveness of the proposed method.

scholarly journals DBac: deadline based data collection using CSMA/CD and earliest deadline first (EDF) scheduling in wireless sensor network

2018 ◽  
Vol 7 (3) ◽  
pp. 1956
Author(s):  
A Felix Arokya Jose ◽  
C Anand Deva Durai ◽  
S John Livingston
Keyword(s):  
Wireless Sensor Network ◽  
Data Collection ◽  
Sensor Network ◽  
Sampling Rate ◽  
Data Communication ◽  
Base Station ◽  
Wireless Sensor ◽  
Earliest Deadline First ◽  
Delivery Ratio ◽  
Earliest Deadline

Wireless Sensor Network (WSN) has an enormous scope of utilizations in detecting different parameters such as temperature, pressure, sound, pollution, etc. The sensed data in each sensor node are a valuable one. To communicate the information to the base station for further processing, a lot of strategies are available. Each sensor senses the data in different sampling rate depending upon the sudden raise in the sensing parameters. Data communication to the base station is very critical due to the dynamicity of the environment during the stipulated time.The sensed data should reach the base station before the data becomes invalid due to the violation of the deadline. In order to avoid deadline violation so that the sensed data becomes useless, this paper proposing a novel data collection algorithm based on the popular Earliest Deadline First (EDF) scheduling algorithm. The various simulation parameters are taken into account to verify the performance of the proposed method and the result shows that it achieves high throughput, low delay, high Packet Delivery Ratio (PDR) and low energy consumption.  

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