Data acquisition

About: Data acquisition is a research topic. Over the lifetime, 37132 publications have been published within this topic receiving 244053 citations.

Remote image capture with centralized processing and storage

Abstract: A system for remote data acquisition and centralized processing and storage is disclosed called the DataTreasury System (600). The DataTreasury System provided comprehensive support for the processing of documents and electronic data associated with different applications including sale, business, banking and general consumer transactions. The system retrieves transaction data such as credit card receipts checks in either electronic or paper form at one or more remote locations, encrypts the data, transmits the encrypted data to a central location, transforms the data to a usable form, performs identification verification using signature data and biometric data, generates informative reports from the data and transmits the informative reports to the remote location(s). The DataTreasury System (200, 400, 600) has many advantageous features which work together to provide high performance, security, reliability, fault tolerance and low cost. First, the network architecture facilitates secure communication between the remote location(s) and the central processing facility. A dynamic address assignment algorithm performs load balancing among the system's servers for faster performance and higher utilization. Finally, partitioning scheme improves the error correction process.

A modular, wireless damage monitoring system for structures

Abstract: A structural monitoring system comprises a plurality of modular, battery powered data acquisition devices which transmit structural information to a central data collection and analysis device over a wireless data link. The data acquisition devices each comprise mechanical vibration sensors, data acquisition circuitry, a digital wireless transmitter, and a battery for providing electrical power to the device. The central data collection device comprises a digital wireless receiver that receives data sent from the data acquisition devices, and a microprocessor for processing the data. A more powerful computer may be interfaced with the central device to provide more sophisticated analysis after a natural hazard or other extreme event. A methodology for operating the monitoring system is also disclosed.

Compressed Sensing Signal and Data Acquisition in Wireless Sensor Networks and Internet of Things

Abstract: The emerging compressed sensing (CS) theory can significantly reduce the number of sampling points that directly corresponds to the volume of data collected, which means that part of the redundant data is never acquired. It makes it possible to create standalone and net-centric applications with fewer resources required in Internet of Things (IoT). CS-based signal and information acquisition/compression paradigm combines the nonlinear reconstruction algorithm and random sampling on a sparse basis that provides a promising approach to compress signal and data in information systems. This paper investigates how CS can provide new insights into data sampling and acquisition in wireless sensor networks and IoT. First, we briefly introduce the CS theory with respect to the sampling and transmission coordination during the network lifetime through providing a compressed sampling process with low computation costs. Then, a CS-based framework is proposed for IoT, in which the end nodes measure, transmit, and store the sampled data in the framework. Then, an efficient cluster-sparse reconstruction algorithm is proposed for in-network compression aiming at more accurate data reconstruction and lower energy efficiency. Performance is evaluated with respect to network size using datasets acquired by a real-life deployment.