Design and Implementation of Monitoring System for Buildin~ Energy Consumption

This paper analyzes the shortcomings of ECOTECT simulation software, puts forward the real-time energy consumption monitoring software. According to the structural characteristics of large public buildings, the paper proposes the key technology development and the functions of the software platform, and provides RS485 communication code. The research results in this paper have some practical value on energy consumption of large-scale construction monitoring.

Optically powered gas monitoring system using single-mode fibre for underground coal mines

We present an optically powered,intrinsically safe gas monitoring system to measure four essential environmental gases(CH_(4),CO_(2),CO and O_(2)),together with ambient temperature and pressure,for underground mines.The system is based on three key technologies developed at UNSW:(1)power-over-fbre(PoF)at 1550 nm using a single industry-standard,low-cost single-mode fbre(SMF)for both power delivery and information transmission,(2)liquid–crystal-based optical transducers for optical telemetry,and(3)ultra-low power consumption design of all electronics.Together,this approach allows each gas monitoring station to operate with less than 150 mW of optical power,meeting the intrinsic safety requirements specifed by the IEC60079-28 standard.A 2-month feld trial at BMA’s Broadmeadow underground mine proved the cabling compatibility to the mine’s existing optical network and the stability of the system performance.Compared with conventional electrically powered gas sensors,this technology bypasses the usual roadblocks of underground gas monitoring where electrical power is either unsafe or unavailable.Furthermore,using one fbre for both power delivery and communication enables longer distance coverage,reduces optical cabling and increases multiplexing possibilities and data throughput for better awareness of underground environment.

Design of a Methane Monitoring System for Landfill and Duct Emissions

Methane is released from waste disposal areas as a result from anaerobic decay of food. Methane causes more greenhouse effects than carbon dioxide so a methane monitoring system is required to warn its release from gas emitting environments. The low explosive limit of methane is 5% in ambient air, so gas leakage is dangerous and can produce explosions. An entire head monitoring system was built around a MQ-4 methane gas sensor as it is cheap and reliable. The design proves to be flexible enough as it can measure CH4 emissions in ducts, CH4 in landfills at different depths and even in cattle barns. The measuring system head consists of a suction pump, solenoids, and a methane sensor. Measurements are taken 13 seconds after methane gas sucking. A timing of 100 seconds is required for purging the chamber before the second solenoid is turned-on. Devices temperature during operation was sampled with a thermal Flir-One camera and solenoid coil temperature was of 24.9˚C after a continuous operation of 30 seconds. As hoses for emission sampling become larger time for sampling increases as well as energy consumption.

Real Time Power Monitoring Detection Based on Sequence Time Domain Reflectometry Approach

Sequence Time Domain Reflectometry (STDR) have been demonstrated to be a powerful technique for detecting the length of cable or length of open circuit or short circuit cables. Using this method along with using smart meter on the main electrical panel board to monitor consumption if load at each circuit, enable user to monitor power consumption at each node (power outlet) only by operating a smart digital meter and an STDR circuitry on each circuit at the main electrical panel board. This paper introduces this method and examines it on dead-wire and energized wire with a load connected across it. Experimental results are demonstrated for both types. Test result show the potential application of this approach to provide consumption information and potential cost saving via feedback for users.

Adaptive Runtime Monitoring of Service Level Agreement Violations in Cloud Computing

The cloud service level agreement(SLA)manage the relationship between service providers and consumers in cloud computing.SLA is an integral and critical part of modern era IT vendors and communication contracts.Due to low cost and flexibility more and more consumers delegate their tasks to cloud providers,the SLA emerges as a key aspect between the consumers and providers.Continuous monitoring of Quality of Service(QoS)attributes is required to implement SLAs because of the complex nature of cloud communication.Many other factors,such as user reliability,satisfaction,and penalty on violations are also taken into account.Currently,there is no such policy of cloud SLA monitoring to minimize SLA violations.In this work,we have proposed a cloud SLA monitoring policy by dividing a monitoring session into two parts,for critical and non-critical parameters.The critical and non-critical parameters will be decided on the interest of the consumer during SLA negotiation.This will help to shape a new comprehensive SLA based Proactive Resource Allocation Approach(RPAA)which will monitor SLA at runtime,analyze the SLA parameters and try to find the possibility of SLA violations.We also have implemented an adaptive system for allocating cloud IT resources based on SLA violations and detection.We have defined two main components of SLA-PRAA i.e.,(a)Handler and(b)Accounting and Billing Manager.We have also described the function of both components through algorithms.The experimental results validate the performance of our proposed method in comparison with state-of-the-art cloud SLA policies.

Design and Implementation of Long-Term Single-Lead ECG Monitor

Some heart diseases need long-term monitoring to diagnose. In this paper, we present a wearable single lead ECG monitoring device with low power consumption based on MSP430 and single-lead ECG front-end AD8232, which could acquire and store patient’s ECG data for 7 days continuously. This device is available for long-term wearing with a small volume. Also, it could detect user’s motion status with an acceleration sensor and supports Bluetooth 4.0 protocol. So it could be expanded to be a dynamic heart rate monitor and/or sleep quality monitor combined with smart phone. The device has huge potential of application for health care of human daily life.

Design and Implementation of an IoT Based Remote Health Monitoring System

Considering the quality of life, manpower, and expenditure, an IoT-based health monitoring system has been proposed and implemented. Devices are placed on the human body to collect data, which is then uploaded to an online data server. Specialist doctors can access this data as needed, allowing them to assess the patient’s initial condition and provide advice at any time. This approach enhances the quality and reach of health services. The module, designed and installed using modern technology, minimizes latency and maximizes data accuracy while reducing delay and battery drain. An accompanying app motivates public acceptance and ease of use. Various sensors, including ECG, SpO2, gyroscope, PIR, temperature-humidity, and BP, collect data processed by an Arduino microcontroller. Data transmission is handled by a WiFi module, with ThingSpeak and Google Sheets used for data processing and storage. The system has been fully tested, and patient data from two hospitals compared with the proposed model shows 97% accuracy.

基于NB-IoT的地下管廊环境监测系统设计

城市地下管廊内布设了大量的管线,如燃气管道、网络通讯线路、电力线路等,由于地下环境复杂多变,存在着气体泄漏、爆炸、火灾等安全风险。针对这些问题,提出一种基于窄带物联网技术(Narrow Band Internet of Things,NB-IoT)的地下管廊环境监测系统。该系统采用先进的传感器技术、NB-IoT技术、软件技术,系统主要分为数据采集模块、物联网云平台、远程监测系统三部分。数据采集模块以STM32作为主控单元连接各个传感器,采集温度、湿度、水位、可燃气体等数据,经过处理后利用NB-IoT网络上传到物联网云平台,远程监测系统调用物联网云平台的数据接口进行远程显示与预警。实验结果表明,系统在降低系统总体功耗的同时,能够实时、稳定地进行地下管廊环境监测,提前预防可能存在的风险。

配置吸收式热泵的热电联产机组厂级智能运行优化

为提高配置吸收式热泵的热电联产机组的全厂运行经济性,基于案例电厂的运行历史数据,使用滑动窗口法进行数据预处理并提取稳态工况,建立配置吸收式热泵的热电联产机组煤耗预测数学模型。以全厂热电联产机组总煤耗最小为适应度函数,利用粒子群优化算法求解得出配置吸收式热泵的热电机组最佳背压和各台热电机组最佳抽汽量。基于以上研究设计了供热系统智能优化软件,实现供热系统在线监测与优化调节,对各供热单元分别提出优化指导,使机组运行经济性最佳,进而降低整体煤耗。计算结果表明:实行供热系统智能优化策略可为案例电厂供热系统平均每小时节省标准煤约1.81 t,节能效果显著。

基于ARIMA模型的校园能耗监测与分析系统的设计与实现

设计了一种基于ARIMA模型(自回归移动平均)的校园能耗监测与分析系统,该系统主要由数据采集、数据存储、预测分析以及数据展示等功能模块组成.研究结果表明,该系统不仅可提升校园能源管理的自动化和智能化水平,而且还可有效提高校园能耗的预测精确度,且优于其他的能耗管理系统;因此,该系统可为提高校园能源使用效率提供良好支持.

基于NB-IoT的智慧健康监测系统设计

人口老龄化导致慢性非传染性的患病率会越来越高,智慧健康养老成为国家应对老龄化的战略目标。针对我国目前的人口结构现状,提出一种基于窄带物联网技术(NB-IoT)的智慧健康监测系统。该系统结合NB-IoT技术、传感器技和软件技术,系统主要包括可穿戴数据采集终端、云服务平台、远程监测平台等3部分。数据采集终端以STM32作为主控制器,实现对用户生理信息的采集,通过NB-IoT网络传输到云平台上,通过远程监测平台实现健康的远程监测,对健康问题进行预警。实验结果表明:系统可以实时采集老年人的生理信息(血压、血氧、心率)、运动轨迹以及定位信息,对老年人进行实时全方位健康监控,提前预防并降低慢性疾病发病率、减小死亡率、延长寿命。

基于数字孪生模型的数字化电网能耗自动监测系统研究

当前使用的数字化电网中,存在感知终端种类较多,对于传统的能耗自动监测系统来说获取的数据传输实时性不足,导致监测结果出现偏差,为此设计一种基于数字孪生模型的数字化电网能耗自动监测系统。系统主要从硬件和软件两方面进行设计:在硬件设计中,根据不同的应用层次,设计系统的总体架构。主要对硬件中的无线通信网络进行搭建,选择基于LoRa无线通信技术的RTU设备作为通信主体。设计LoRa无线开关电路,实现ZigBee设备之间的无线数据传输和交换;软件设计中,设计能耗数据采集主线程,分析数字孪生模型映射交互关系,基于数字孪生模型与实际运行工况之间的映射关系实现能耗指标实时监测。实验结果表明,与传统系统相比,设计得到的检测结果与实际的能耗情况更加相符。

校园能耗监控系统的设计与实现

为实现校园能耗监控,指出了高效能耗监测系统存在的问题,包括能耗消费水平高、能源使用形式复杂、未形成能源效率评价体系等。提出校园能耗监测系统技术优化方案,设计了一套由物联网、云计算、传感技术融合而成的校园能耗监控系统,对其进行分类整理,对总体结构与技术要求进行分析,为校园能耗监控系统的技术革新提供参考。

基于STM32的低功耗高精度智能体温无线检测系统

文章设计了以STM32L051C8T6单片机为核心的低功耗高精度智能体温无线检测系统,实现了高精度的体温监测、人性化智能语音播报、稳定的无线传输、低功耗电源管理等功能。该系统传输稳定,抗干扰能力强,续航持久,低辐射,为父母照顾生病发烧的婴幼儿提供了便利。本系统落实科技改变生活,顺应时代发展,解决千万父母的疑难问题。

基于GPS数据的实验室制氢废液污染实时监测

为了提高制氢废液污染监测效果,文中提出基于GPS数据的实验室制氢废液污染实时监测方法。利用GPS系统采集污染数据,通过串口读取GPS数据,定位污染位置。以降低监测能耗为目的,采用在线监测机制和短信通知监测相互转换形式实现实验室制氢废液污染实时监测。结合GPS、GPRS、GIS三种技术对监测所得数据进行管理与分析,为实验室制氢废液污染治理提供技术支持。通过实际应用结果表明,文中设计方法监测能耗较低,安全性强,监测数据传输效率较高,证明所提方法具有较好的应用性能,可用于实验室制氢废液污染的实时监测。

基于多传感器数据自动融合的配电房能耗远程监控系统

为了全面、准确地监测配电房能耗,设计了基于多传感器数据自动融合的配电房能耗远程监控系统。硬件上,采用A1101R04C霍尔传感器、DC 0~20 V电压传感器、SINAEX P530功率传感器及DHT11温湿度传感器设计传感器模块,并选择STM32F407ZGT芯片作为微处理器。软件上,采集配电房传感器监测数据,基于多传感器数据自动融合算法进行不同传感器监测数据的融合,获取配电房能耗监控结果。结果表明,配电房能耗远程监控数据的误差在±1%范围内,具有较高的监测精度和稳定性。

面向实验动物设施的能耗监测系统设计与应用

目的 实验动物设施的能源消耗在科研机构能耗中占据相当大的比例,且其能耗特点与普通建筑物存在显著不同,因而需要专门的监测与管理。方法 面向实验动物设施设计了一套能耗监测系统,选取华中科技大学SPF级实验动物设施进行了部署。结果 该系统上线运行后,实现了设施用电量数据的实时采集和记录,并提出了3种应用场景下的管理节能措施。结论 面向实验动物设施的能耗监测系统具备可靠、高效、易用的特点,对实验动物设施能源管理工作具有指导意义与推广价值。

基于统计过程控制的药品用量动态监测研究

目的 探索基于统计过程控制(SPC)的药品用量动态监测方法,以提升药品使用过程的宏观监管水平。方法 根据药品费用和国家相关文件建立我院重点监控药品品种目录。以全院、门诊药房和住院药房的重点监控药品品种月度用量数据为监测对象,利用SPC的X控制图、移动极差控制图和指数加权移动平均值控制图建立药品用量动态监测(DMDC)模型,分别从单月用量、极差变化以及用量趋势3个维度进行监测。以瑞舒伐他汀、美托洛尔和美罗培南为例,展示DMDC模型的监测效果。结果 针对全院、门诊药房和住院药房分别建立了包含203、167和200个品种的重点监控药品目录。在排除无法建模及建模失败的品种后,成功为这3个药品消耗区域分别建立了179、116和172个DMDC模型。这3组模型在2024年前4个月的实践中,警示的药品品种数分别为54、32、62个。所建DMDC模型成功监测了全院瑞舒伐他汀、门诊药房美托洛尔以及住院药房美罗培南等药品的月度用量。相较于我院原用的浮动率排序法,DMDC模型的应用显著提升了药品监测的范围和深度,监测品种由原先的约50种大幅扩展至179种,监测维度也从1个维度增加到了3个维度。结论 基于SPC的DMDC模型有效、可行,适用于对月度用量较稳定的药品品种进行监测。

面向外骨骼性能评估的多源生理能耗预测

在外骨骼设计过程中,助力性能评估直接影响整体结构的安全性和效率.针对目前性能评估多采用单一指标问题,提出了一种基于多源生理信号(表面肌电、脉搏和呼吸)的长短期记忆(long short-term memory,LSTM)网络运动能耗预测方法.该方法首先对生理信号进行处理和特征提取,然后使用6层LSTM模型进行预测,并使用K折交叉验证方法进行验证.同时,与决策树(decision tree,DT)和支持向量机(support vector machine,SVM)进行了对比实验.最后,建立了在线能耗监测系统,作为评估外骨骼助力性能的依据.结果表明,三源信号均方根差(root mean square error,RMSE)为0.073 kJ,证明了采用多源生理信号融合预测的可行性;LSTM的RMSE相较于DT,SVM下降了39.53%,15.68%,测试集的总能耗值误差值为23.98kJ,说明LSTM模型对于总能耗预测效果最好,可用于外骨骼的助力性能评估.

低功耗可穿戴式心电监测系统

日常心电监测对预防心血管病具有重要意义,但医用心电监测系统成本高、操作复杂且不适用于居家心电监测,可穿戴设备忽视了噪声干扰问题,难以利用采集信号来分析诊断病情。文中设计了一种低功耗可穿戴式心电监测系统,该系统由电源管理模块、心电采集模块、数据处理模块和延时开关模块4部分组成,通过BMD101芯片采集人体心电信号,使用低功耗蓝牙芯片nrf52832将心电数据发送到移动端。针对信号中易引入的肌电干扰噪声问题,文中提出了基于变分模态分解(Variational Mode Decomposition,VMD)的去噪算法,利用非局部均值(Non-Local Mean,NLM)滤除心电信号中低频模态的噪声,离散小波(Discrete Wavelet Transform,DWT)阈值去噪算法消除心电信号的高频模态噪声,重构后的信号质量明显提高。实验结果证明,所提算法具有成本低、易便携和使用方便等特点,能够获取高质量的心电信号,满足用户的长程监测需求,解决了日常不方便监测心电和心电信号获取质量低的问题。