An application of metadata-based image retrieval system for facility management

For facility management, photography is an efficient and accurate method of recording the physical state of infrastructure. However, without an effective organizational scheme, the difficulty of retrieving relevant photos from historical databases can become overly burdensome for highly complex or long-lived assets. To make strategic decisions, it is crucial to retrieve the right information from a plurality of sources in a timely manner. The main objective of this paper is to present a method for organizing and retrieving photos from massive facility management photo databases using photo-metadata: photographed location, camera perspective, and image semantic content information. Indoor localization experiments were performed using Bluetooth technology to infer the location information. Perspective is inferred from the device’s on-board inertial measurement unit (IMU). Image semantic content is inferred using a Convolutional Neural Network (CNN)-based deep learning algorithm. Fusing these three features, seven query options were provided for the user when retrieving images. Leveraging Building Information Modeling (BIM) as a process and Geographic Information Systems (GIS) as a framework, this paper also envisions a federated information management by connecting 2D and 3D facility assets with our real-world map which can be smoothly bridged with our image retrieval system. The realization of the integrated application with BIM and GIS is significantly beneficial for the facility management domain by advancing the understanding of projects in a broader view with a federated data platform. In this research, the framework is illustrated with 21 institutional buildings within the University of Texas at Austin’s main campus, and the authors conclude that the proposed metadata-based image retrieval system can ultimately enhance the better-informed decision-making process through rapid information retrieval.     

An IoT-Aware System for Managing Patients’ Waiting Time Using Bluetooth Low-Energy Technology

It is a common observation that whenever patients arrives at the front desk of a hospital, outpatient clinic, or other health-associated centers, they have to first queue up in a line and wait to fill in their registration form to get admitted. The long waiting time without any status updates is the most common complaint, concerning health officials. In this paper, UrNext, a location-aware mobile-based solution using Bluetooth low-energy (BLE) technology is presented to solve the problem. Recently, a technology-oriented method, the Internet of Things (IoT), has been gaining popularity in helping to solve some of the healthcare sector’s problems. The implementation of this solution could be illustrated through a simple example of when a patient arrives at a clinic for a consultation. Instead of having to wait in long lines, that patient will be greeted automatically, receive a push notification of an admittance along with an estimated waiting time for a consultation session. This will not only provide the patients with a sense of freedom but would also reduce the uncertainty levels that are generally observed, thus saving both time and money. This work aims to improve the clinics’ quality of services, organize queues and minimize waiting times, leading to patients’ comfort while reducing the burden on nurses and receptionists. The results demonstrate that the presented system is successful in its performance and helps achieves a pleasant and conducive clinic visitation process with higher productivity.     

智能手机蓝牙抄表设计方案

目前,在我国的电力、燃气、热力、自来水行业,大部分仍然采用无线远程集抄和手持抄表机的人工抄表模式。随着智能手机的普及,手机的功能和质量已经远远强于一般的数据采集手持设备。使用手机抄表软件可以轻松实现日常数据采集抄录工作。并可以使用手机的网络实现数据的及时上传下载。本文提供一种用于热量表的智能手机蓝牙抄表的抄收方法,该方法实现使用一部普通的android智能手机实现对热量表的抄读和设置。由于采取通用的智能手机平台,不依赖硬件设备,不需要定制产品,只需要额外加一个蓝牙转串口模块、采用相同的手机操作系统程序代码就可以通用,智能手机平台在编程工具方面都具有很好的扩展性,本方法在功能上扩展性强;智能手机平台在通信通道上有较强的延伸性,能够依照本方法搭建很好的解决方案,进行数据通信等。     

基于STM32的智能笔筒设计

针对现在流行笔筒功能单一、缺少互动、人性化程度低等问题,介绍了一种基于STM32单片机的智能笔筒的设计与实现方法。该设计将电子元素与古朴笔筒有机结合,采用集成化的硬件设计方案,包括液晶显示、人体感应、MP3解码和文件存储等模块,支持热插拔,并可通过蓝牙与Android或IOS 智能设备进行数据交互,使用者可根据自身需求,个性化地设置属于自己的笔筒。     

医用诊断X光机管电流测试系统的设计与实现

X光机管电流作为控制X射线强度的重要参数,已被包含在JJG 744 - 2004《医用诊断X射线辐射源》国家计量检定规程中.随着数字诊断治疗水平的不断发展,传统电流表已不能准确测量X光机管电流与曝光时间,为了保障医用X光机安全可靠运行,提高与之相应的数字化检测水平,设计验证了一套包含高速ADC与FPGA结合的数字化采样...     

蓝牙无线个域网及其流量特性分析

对蓝牙无线个域网的各项流量特性进行了分析,探讨了蓝牙设备在4种工作模式间的切换对蓝牙网络性能的影响,分析了影响蓝牙网络有效带宽的各个因素。另外,通过仿真,发现蓝牙无线链路流量特性具有自相似的特性,即适合采用自相似类型的流量模型来进行分析、描述及预测。     

2.4GHz产品巴西Anatel认证的RF要求

详细介绍了巴西Anatel认证RF测试部分对于蓝牙和Wi-Fi 802.11b＋g产品的要求和测试方法,并对于各个测试项目在实际测试中需要注意的问题进行解析,最后分析了相关通用国际标准在认证中的适用性。     

ARM与上位机的蓝牙通信系统设计

针对某型导弹装备嵌入式数据采集系统与上位机的通信受复杂环境影响大,不稳定和布线不便的问题,采用CSR公司新一代蓝牙芯片,设计了二者之间的蓝牙通信系统。给出了蓝牙通信系统的总体实现方案,软硬件结构框图。系统由ARM与蓝牙芯片接口电路和上位机与蓝牙芯片接口电路组成。测试结果表明,二者之间的通信不再受复杂环境的影响,数据传输稳定,可靠性高,通信更为方便。     

基于Android的交通信号机手持终端软件设计与实现

针对路口交通信号设置不便的问题,研究了基于Android开发平台的交通信号机手持终端软件的设计与实现过程,该软件使用Android软件开发工具包和Eclipse集成开发环境进行开发,具有常用设置、特殊设置、打开文件和保存文件等功能。交通管理人员可以用Android智能手机作为信号机手持终端,与信号机通过蓝牙连接,方便地对交通信号参数进行设置。     

无线传感器网络通信技术与标准化分析

通过分析现有无线传感器网络标准,并对Zig Bee、蓝牙以及Wi-Fi这3种最常用标准的优缺点进行详细比较,探讨了无线传感器网络通信技术面临的挑战,进一步研究策略和未来发展趋势。