3,284 research outputs found

    A WI-FI BASED SMART DATA LOGGER FOR CAPSULE ENDOSCOPY AND MEDICAL APPLICATIONS

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    Wireless capsule endoscopy (WCE) is a non-invasive technology for capturing images of a human digestive system for medical diagnostics purpose. With WCE, the patient swallows a miniature capsule with camera, data processing unit, RF transmitter and batteries. The capsule captures and transmits images wirelessly from inside the human gastrointestinal (GI) tract. The external data logger worn by the patient stores the images and is later on transferred to a computer for presentation and image analysis. In this research, we designed and built a Wi-Fi based, low cost, miniature, versatile wearable data logger. The data logger is used with Wi-Fi enabled smart devices, smart phones and data servers to store and present images captured by capsule. The proposed data logger is designed to work with wireless capsule endoscopy and other biosensors like- temperature and heart rate sensors. The data logger is small enough to carry and conduct daily activities, and the patient do not need to carry traditional bulky data recorder all the time during diagnosis. The doctors can remotely access data and analyze the images from capsule endoscopy using remote access feature of the data logger. Smartphones and tablets have extensive processing power with expandable memory. This research exploits those capabilities to use with wireless capsule endoscopy and medical data logging applications. The application- specific data recorders are replaced by the proposed Wi-Fi data logger and smartphone. The data processing application is distributed on smart devices like smartphone /tablets and data logger. Once data are stored in smart devices, the data can be accessed remotely, distributed to the cloud and shared within networks to enable telemedicine. The data logger can work in both standalone and network mode. In the normal mode of the device, data logger stores medical data locally into a micro Secure Digital card for future download using the universal serial bus to the computer. In network mode, the real-time data is streamed into a smartphone and tablet for further processing and storage. The proposed Wi-Fi based data logger is prototyped in the lab and tested with the capsule hardware developed in our laboratory. The supporting Android app is also developed to collect data from the data logger and present the processed data to the viewer. The PC based software is also developed to access the data recorder and capture and download data from the data logger in real-time remotely. Both in vivo and ex vivo trials using live pig have been conducted to validate the performance of the proposed device

    Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

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    INE/AUTC 10.0

    Experiences and issues for environmental engineering sensor network deployments

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    Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

    Experiences and issues for environmental science sensor network deployments

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    Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

    Embedded Trusted Monitoring and Management Modules for Smart Solar Panels

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    This paper investigates developing a prototype of smart solar panels. This architecture consists of a panel monitoring module and the central management unit. The monitoring module is to be embedded inside each PV panel making it secure to transfer the trusted data via Wi-Fi to the central Management unit (which can accommodate an array of PV panels in an installation). This module is required for data storage and provides the ability to upload secure data to the cloud. This platform presents the ability to securely manage large numbers of rooftop solar panels in a distributed ledger by implementing block chain algorithm. For achieving this purpose, Module 400 is envisaged to be turned into a Blockchain node as it provides the infrastructure to implement this technology

    Investigating rock mass failure precursors using a multi-sensor monitoring system. Preliminary results from a test-site (Acuto, Italy)

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    In the last few years, several approaches and methods have been proposed to improve early warning systems for managing risks due to rapid slope failures where important infrastructures are the main exposed elements. To this aim, a multi-sensor monitoring system has been installed in an abandoned quarry at Acuto (central Italy) to realise a natural-scale test site for detecting rock-falls from a cliff slope. The installed multi-sensor monitoring system consists of: i) two weather stations; ii) optical cam (Smart Camera) connected to an Artificial Intelligence (AI) system; iii) stress- strain geotechnical system; iv) seismic monitoring device and nano-seismic array for detecting microseismic events on the cliff slope. The main objective of the experiment at this test site is to investigate precursors of rock mass failures by coupling remote and local sensors. The integrated monitoring system is devoted to record strain rates of rock mass joints, capturing their variations as an effect of forcing actions, which are the temperature, the rainfalls and the wind velocity and direction. The preliminary tests demonstrate that the data analysis methods allowed the identification of external destabilizing actions responsible for strain effects on rock joints. More in particular, it was observed that the temperature variations play a significant role for detectable strains of rock mass joints. The preliminary results obtained so far encourage further experiments

    Simultaneously connecting devices through bluetooth smart

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    Modern data loggers record and store large amounts of data from many different types of sensors. This enables their use in various applications to capture different measurands. However wireless access to the recorded data opens countless possibilities for novel and innovative applications, for example in the health monitoring of humans or livestock. In many of these applications a central device connects simultaneously to several data loggers. This paper discusses the experiences made during the design, implementation and test of an energy efficient wireless interface to a data logger. The implemented system serves as an application example for Bluetooth Smart. It allows a user to monitor ongoing measurements of several data loggers through a smartphone. Additionally the recorded data of several loggers can be simultaneously uploaded to a central gateway. The available Bluetooth Smart chips and software stacks place limitations on usable bandwidth as well as on the number of simultaneous connections. Although most modern smartphones include hardware for Bluetooth Smart, implementations differ widely across platforms, thus creating additional effort for the app programmer. This paper presents measurement results and introduces the implemented approaches to optimize these parameters

    Design and Implementation of Wireless Sensors and Android Based Application for Highly Efficient Aquaculture Management System

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    The main problems in the practice of traditional shrimp aquaculture are related with maintaining good water quality and reducing high operational cost. In this paper it will be described the application of wireless sensors and Android based application as mobile monitoring tool in achieving highly efficient shrimp aquaculture monitoring system. A set of four water quality parameter sensors (pH, temperature, conductivity and DO) were submerged into the pond using a buoy, in which an electronics and Xbee wireless transmitter have been installed to transmit the measured data into a fixed monitoring station. The main component of the fixed monitoring station was a smart data logger capable of performing automatic aeration system. Data transmission from the monitoring station to the master station was done through GSM/GPRS module of a Raspberry microcontroller. Using internet connection, a web based server has been developed from which the Android based application retrieved the measured parameter data. Graphical analysis of water quality data can be performed from a mobile phone, allowing users to monitor the aquaculture regardless of their geographical location. This system has been implemented in a shrimp aquaculture in Bangka island, Indonesia. In addition to giving real-time water quality data, the system was able to reduce the operational electricity cost because of the automatic aeration feature. Consistenly, the system has been sending the measurement data to the web server, which is accessible using Android mobile phones worldwide
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