Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.

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High-accuracy Position-aware Robot for Agricultural Automation using Low-cost IMU-coupled Triple-laser-guided (TLG) System

IEEE Access ◽

10.1109/access.2021.3071554 ◽

2021 ◽

pp. 1-1

Author(s):

Kaewkorn Supod ◽

Ekpanyapong Mongkol ◽

Thamma Ukrit

Keyword(s):

Low Cost ◽

High Accuracy

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Deep Learning-based Selection Strategy of Polling Switch for Low-cost and High-accuracy Flow Statistics Collection in SDN

2020 International Conference on Internet of Things and Intelligent Applications (ITIA) ◽

10.1109/itia50152.2020.9312376 ◽

2020 ◽

Author(s):

Zhigeng Han ◽

Yiru Yao

Keyword(s):

Deep Learning ◽

Low Cost ◽

High Accuracy ◽

Selection Strategy

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High accuracy low-cost videogrammetric system: an application to 6DOF estimation of ship models

10.1117/12.2020922 ◽

2013 ◽

Author(s):

Erica Nocerino ◽

Fabio Menna ◽

Salvatore Troisi

Keyword(s):

Low Cost ◽

High Accuracy

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A primal-dual algorithm for data gathering based on matrix completion for Wireless Sensor Networks

2016 IEEE International Conference on Communications (ICC) ◽

10.1109/icc.2016.7511420 ◽

2016 ◽

Cited By ~ 1

Author(s):

Mohamed-Ali Moussa ◽

Yosra Marnissi ◽

Yacine Ghamri-Doudane

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Matrix Completion ◽

Data Gathering ◽

Wireless Sensor ◽

Dual Algorithm ◽

Primal Dual

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Design and Implement of High-Accuracy On-Line Metal Thickness Measuring Instrument Based on NiosII Processor

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.834-836.930 ◽

2013 ◽

Vol 834-836 ◽

pp. 930-934

Author(s):

Shou Liang Yang ◽

Bao Liang Yang

Keyword(s):

Eddy Current ◽

Low Cost ◽

High Accuracy ◽

Resolving Power ◽

Current Sensor ◽

Measuring Instrument ◽

Precision Data ◽

Eddy Current Sensor ◽

Metal Thickness ◽

On Line

The paper proposes a new design of high-accuracy On-line Metal Thickness Measuring Instrument, which was based on EP2C20 series FPGA chip, through adding NiosII soft processor and other interfaces to FPGA, equipped with high precision data collection system and TFT LCD module and so on. The key hardware blocks schematics and components of the RC Oscillation Circuit,eddy current sensor Circuit,rectifier and filter Circuit,A/D converting circuit,FPGA Circuit are described,software flow charts and sample codes are given. According to practice, The measurement range of this system is 1~100 mm and the resolving power is 0.1 μm. degree of linearity is 1%, The system has many features including small volume of hardware, low cost, high detecting precision, convenient operating, high intelligent and so on, leading to broad and bright future. Key words: NiosII processor; eddy current sensor; metal thickness

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Design and Development of a 5-Channel Arduino-Based Data Acquisition System (ABDAS) for Experimental Aerodynamics Research

Sensors ◽

10.3390/s18072382 ◽

2018 ◽

Vol 18 (7) ◽

pp. 2382 ◽

Cited By ~ 12

Author(s):

Antonio Vidal-Pardo ◽

Santiago Pindado

Keyword(s):

Data Acquisition ◽

Low Cost ◽

Data Acquisition System ◽

High Accuracy ◽

Acquisition System ◽

Calibration System ◽

Experimental Aerodynamics ◽

Accuracy Level ◽

The Fourier Transform ◽

Cup Anemometer

In this work, a new and low-cost Arduino-Based Data Acquisition System (ABDAS) for use in an aerodynamics lab is developed. Its design is simple and reliable. The accuracy of the system has been checked by being directly compared with a commercial and high accuracy level hardware from National Instruments. Furthermore, ABDAS has been compared to the accredited calibration system in the IDR/UPM Institute, its measurements during this testing campaign being used to analyzed two different cup anemometer frequency determination procedures: counting pulses and the Fourier transform. The results indicate a more accurate transfer function of the cup anemometers when counting pulses procedure is used.

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REGIONAL NETWORK FOR COASTAL ENGINEERING DATA

Coastal Engineering Proceedings ◽

10.9753/icce.v15.5 ◽

1976 ◽

Vol 1 (15) ◽

pp. 5

Author(s):

Richard J. Seymour ◽

Meredith H. Sessions

Keyword(s):

Numerical Models ◽

Meteorological Data ◽

Low Cost ◽

Data Gathering ◽

Monitoring Network ◽

Beach Erosion ◽

Direct Result ◽

Ocean Engineering ◽

California Department ◽

La Jolla

The California Department of Navigation and Ocean Development (DNOD), responsible for shoreline protection within the state, was particularly aware of the lack of coastal wave statistics to support their beach erosion program. As a direct result of the 1974 ASCE-sponsored New Orleans Conference on Ocean Wave Measurement and Analysis, discussion was initiated within DNOD and then with the Scripps Institution of Oceanography (SIO) at La Jolla, on the feasibility o"f establishing a regional wave monitoring network for California. The initial specification presented by DNOD was for a 200-station network reporting directional wave spectra twice daily for a period of ten years. SIO ocean engineering personnel responded with a system concept employing low-cost pressure transducers hardwired to shore with a dialup telephone data gathering link to a central station. The initial cost estimates appeared attractive when compared with Corps of Engineers experience as reported in Peacock (1974). As a result, a small program was funded in February 1975 at Scripps to demonstrate critical hardware items through the breadboard stage. With the successful completion of this work, additional funds were allocated by DNOD as matching funds for a California Sea Grant Project. Th_e first station in the network began operation on 3 December 1975 at Imperial Beach, California. A second station was added at Ocean Beach (San Diego) on 27 March 1976, a third at SIO (La Jolla) on 18 May 1976 and the fourth at Oceanside, California on 2 June 1976. The locations of these initial stations are shown in Figure 1. Considerable effort has been directed during the past 10 years toward the development of numerical models to predict deep-water wave conditions from meteorological data. Reasonable results have been obtained and sufficient accuracy achieved to allow routing of both commercial and military ship traffic.

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