Bringing Life Where There Is No Light: A Low-Cost Movie Projection and Data Collection Solution for Underserved Areas

2018 ◽  
pp. 90-99
Author(s):  
Alain Shema ◽  
Michel Bézy
Keyword(s):  
Data Collection ◽  
Low Cost

Development of Low Cost, Rapid Sampling Atmospheric Data Collection System: Part 2 - Sensor & System Integration

2021 ◽  
Author(s):  
Andrew L. Ross ◽  
Victoria A. Natalie ◽  
James C. Brenner ◽  
Kyle T. Hickman ◽  
Jamey D. Jacob
Keyword(s):  
Data Collection ◽  
System Integration ◽  
Low Cost ◽  
Sensor System ◽  
Collection System ◽  
Data Collection System ◽  
Rapid Sampling ◽  
Atmospheric Data ◽  
System Part

scholarly journals Analisis Pengaruh Brand Image, Harga, Dan Kualitas Produk Terhadap Keputusan Pembelian Mobil (Studi Kasus Mobil LCGC di Surakarta)

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Budi Istiyanto, Lailatan Nugroho
Keyword(s):  
Data Collection ◽  
Multiple Regression ◽  
Brand Image ◽  
Low Cost ◽  
Purchase Decision ◽  
Purchasing Decisions ◽  
Quality Product ◽  
Quality Of Products

AbstractThis study aimed to determine the effect of variable brand image, price, quality of product to decision of purchasing a car LCGC (Low Cost Green Car), either partial or jointly and to find among variables brand image, price, and quality of products which are larger role in influencing purchasing decisions LCGC car. Data collection techniques researchers did by observation and questionnaires directly by visiting the object of the research is to consumers who have made a purchase decision, especially type Agya LCGC car, AYLA, and Karimun Wagon R in Surakarta which would then be sampled. The data have been collected and tabulated and analyzed using multiple regression analysis.The results showed that the variables that significantly affect purchasing decisions is price and quality of products. While the variable Brand Image does not affect significantly. While the variables that affect predominantly variable price.Keyword: Brand Image, Price, Quality Product, Purchase Decision AbstrakPenelitian ini bertujuan untuk mengetahui pengaruh antara variable brand image, harga, dan kualitas produk terhadap keputusan pembelian mobil LCGC (Low Cost Green Car) baik secara partial maupun secara bersama-sama dan untuk mengetahui diantara variable brand image, harga, dan kualitas produk mana yang lebih berperan dalam mempengaruhi keputusan pembelian mobil LCGC. Teknik pengumpulan data peneliti lakukan dengan cara observasi dan penyebaran kuisioner secara langsung dengan cara mendatangi obyek penelitian yaitu kepada konsumen yang telah melakukan keputusan pembelian mobil LCGC terutama type AGYA,AYLA, dan Karimun Wagon R di wilayah Surakarta yang selanjutnya akan dijadikan sampel. Data yang telah terkumpul kemudian ditabulasi dan diolah dengan menggunakan analisis regresi berganda.Hasil penelitian menunjukkan bahwa variabel yang mempengaruhi secara signifikan keputusan pembelian adalah harga dan kualitas produk. Sedangkan variabel Brand Image tidak mempengaruhi secara signifikan. Sedangkan variabel yang berpengaruh secara dominan adalah variabel harga.Kata kunci: Brand Image, Harga, Kualitas Produk, Keputusan Pembelian

scholarly journals Data Gathering from a Multimodal Dense Underwater Acoustic Sensor Network Deployed in Shallow Fresh Water Scenarios

2019 ◽  
Vol 8 (4) ◽  
pp. 55 ◽  
Author(s):  
Alberto Signori ◽  
Filippo Campagnaro ◽  
Fabian Steinmetz ◽  
Bernd-Christian Renner ◽  
Michele Zorzi
Keyword(s):  
Data Collection ◽  
Low Cost ◽  
World Ocean ◽  
Environmental Data ◽  
Sensor Nodes ◽  
Real Field ◽  
Acoustic Sensor ◽  
Adaptive Mechanism ◽  
Underwater Acoustic ◽  
Inspection Service

The Robotic Vessels as-a-Service (RoboVaaS) project intends to exploit the most advanced communication and marine vehicle technologies to revolutionize shipping and near-shore operations, offering on-demand and cost-effective robotic-aided services. In particular, the RoboVaaS vision includes a ship hull inspection service, a quay walls inspection service, an antigrounding service, and an environmental and bathymetry data collection service. In this paper, we present a study of the underwater environmental data collection service, performed by a low-cost autonomous vehicle equipped with both a commercial modem and a very low-cost acoustic modem prototype, the smartPORT Acoustic Underwater Modem (AHOI). The vehicle mules the data from a network of low cost submerged acoustic sensor nodes to a surface sink. To this end, an underwater acoustic network composed by both static and moving nodes has been implemented and simulated with the DESERT Underwater Framework, where the performance of the AHOI modem has been mapped in the form of lookup tables. The performance of the AHOI modem has been measured near the Port of Hamburg, where the RoboVaaS concept will be demonstrated with a real field evaluation. The transmission with the commercial modem, instead, has been simulated with the Bellhop ray tracer thanks to the World Ocean Simulation System (WOSS), by considering both the bathymetry and the sound speed profile of the Port of Hamburg. The set up of the polling-based MAC protocol parameters, such as the maximum backoff time of the sensor nodes, appears to be crucial for the network performance, in particular for the low-cost low-rate modems. In this work, to tune the maximum backoff time during the data collection mission, an adaptive mechanism has been implemented. Specifically, the maximum backoff time is updated based on the network density. This adaptive mechanism results in an 8% improvement of the network throughput.

Low-Cost Expendable Buoys for Under Ice Data Collection

2018 ◽  
Author(s):  
D. Langis ◽  
P. J. Stabeno ◽  
C. Meinig ◽  
C. W. Mordy ◽  
S. W. Bell ◽  
...  
Keyword(s):  
Data Collection ◽  
Low Cost

More Data or Better Data? A Statistical Decision Problem

2017 ◽  
Vol 84 (4) ◽  
pp. 1583-1605 ◽  
Author(s):  
Jeff Dominitz ◽  
Charles F. Manski
Keyword(s):  
Data Collection ◽  
Decision Problem ◽  
Low Cost ◽  
Statistical Decision Theory ◽  
Sample Design ◽  
Statistical Decision ◽  
Finite Samples ◽  
Statistical Decision Problem ◽  
Sample Member

AbstractWhen designing data collection, crucial questions arise regarding how much data to collect and how much effort to expend to enhance the quality of the collected data. To make choice of sample design a coherent subject of study, it is desirable to specify an explicit decision problem. We use the Wald framework of statistical decision theory to study allocation of a budget between two or more sampling processes. These processes all draw random samples from a population of interest and aim to collect data that are informative about the sample realizations of an outcome. They differ in the cost of data collection and the quality of the data obtained. One may incur lower cost per sample member but yield lower data quality than another. Increasing the allocation of budget to a low-cost process yields more data, while increasing the allocation to a high-cost process yields better data. We initially view the concept of “better data” abstractly and then fix attention on two important cases. In both cases, a high-cost sampling process accurately measures the outcome of each sample member. The cases differ in the data yielded by a low-cost process. In one, the low-cost process has non-response and in the other it provides a low-resolution interval measure of each sample member’s outcome. In these settings, we study minimax-regret sample design for prediction of a real-valued outcome under square loss; that is, design which minimizes maximum mean square error. The analysis imposes no assumptions that restrict the unobserved outcomes. Hence, the decision maker must cope with both the statistical imprecision of finite samples and the partial identification of the true state of nature.

scholarly journals Design and implementation of data collection module for WSN application

2015 ◽  
Vol 4 (1) ◽  
pp. 104
Author(s):  
Valentina Markova ◽  
Teodora Trifonova ◽  
Venceslav Draganov
Keyword(s):  
Data Collection ◽  
Power Management ◽  
Low Cost ◽  
Wireless Sensor ◽  
Remote Monitoring System ◽  
Design And Implementation ◽  
System A ◽  
Monitoring Applications ◽  
Reliable Performance ◽  
Proper Operation

This paper presents the design and implementation of universal low cost data collection module (DCM), which is an essential part of remote monitoring system based on wireless sensor network. The proposed module expands the capabilities of a measuring node for collecting data from greater number of sensors. The DCM includes four parts: one group multiplexers for data acquisition, second group multiplexers for power management, voltage to current converters and DC/DC converters. The universal DC/DC converters provide autonomous power supply for the sensors and the multiplexers, which can be turned on or off for a certain period of time. The data collecting, monitoring and logging functions are realized through a LabVIEW project.The proper operation and the reliable performance of the system were proved by practical experiment. The proposed module makes the WSN-based system a versatile solution for a variety of monitoring applications.

scholarly journals Design and Implementation of a Connection between Augmented Reality and Sensors

Robotics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 3
Author(s):  
Marlon Aguero ◽  
Dilendra Maharjan ◽  
Maria del Pilar Rodriguez ◽  
David Dennis Lee Mascarenas ◽  
Fernando Moreu
Keyword(s):  
Augmented Reality ◽  
Data Collection ◽  
Real Time ◽  
Strain Gauge ◽  
Low Cost ◽  
Contextual Information ◽  
Wireless Sensor ◽  
Infrastructure Management ◽  
Data Collection And Analysis ◽  
The Way

Wireless sensor networks (WSN) are used by engineers to record the behavior of structures. The sensors provide data to be used by engineers to make informed choices and prioritize decisions concerning maintenance procedures, required repairs, and potential infrastructure replacements. However, reliable data collection in the field remains a challenge. The information obtained by the sensors in the field frequently needs further processing, either at the decision-making headquarters or in the office. Although WSN allows data collection and analysis, there is often a gap between WSN data analysis results and the way decisions are made in industry. The industry depends on inspectors’ decisions, so it is of vital necessity to improve the inspectors’ access in the field to data collected from sensors. This paper presents the results of an experiment that shows the way Augmented Reality (AR) may improve the availability of WSN data to inspectors. AR is a tool which overlays the known attributes of an object with the corresponding position on the headset screen. In this way, it allows the integration of reality with a virtual representation provided by a computer in real time. These additional synthetic overlays supply data that may be unavailable otherwise, but it may also display additional contextual information. The experiment reported in this paper involves the application of a smart Strain Gauge Platform, which automatically measures strain for different applications, using a wireless sensor. In this experiment, an AR headset was used to improve actionable data visualization. The results of the reported experiment indicate that since the AR headset makes it possible to visualize information collected from the sensors in a graphic form in real time, it enables automatic, effective, reliable, and instant communication from a smart low-cost sensor strain gauge to a database. Moreover, it allows inspectors to observe augmented data and compare it across time and space, which then leads to appropriate prioritization of infrastructure management decisions based on accurate observations.

The Smart Three-Phase Electric Meter Based on ENC28J60 and MSP430F149

2011 ◽  
Vol 211-212 ◽  
pp. 1230-1234
Author(s):  
Wen Hua Zhou ◽  
Xiao Long Chen
Keyword(s):  
Data Collection ◽  
Low Cost ◽  
Development Trend ◽  
Power Measurement ◽  
Collection System ◽  
Smart Power ◽  
Data Collection System ◽  
Remote Transmission ◽  
Three Phase ◽  
Power Enterprise

The electric meter is a direct tool by which power enterprise charges for electricity Tariff. This paper describes software and hardware designs of MSP430F149 SCM as the core control processor and smart remote transmission three-phase electric meter with the use of power collection special chip CS5460A to complete power measurement. This instrument integrates data monitoring and measurement of the power with LCD. And it can realize the functions of data remote transmission through communication connection between ENC28J60 chip and main controller and easily of real-time monitoring, data collection, system monitoring. This electric meter has some advantages such as powerful function, low cost, strong disturb-resistant ability, etc. and can meet the management requirement of the electricity energy intelligence, which is one of the main development trend in the future. This smart power data collection system will get a good application in the power industry informatization process .

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