Long-Term Techno-Economic Performance Monitoring to Promote Built Environment Decarbonisation and Digital Transformation—A Case Study

Buildings’ long-term techno-economic performance monitoring is critical for benchmarking in order to reduce costs and environmental impact while providing adequate services. Reliable building stock performance data provide a fundamental knowledge foundation for evidence-based energy efficiency interventions and decarbonisation strategies. Simply put, an adequate understanding of building performance is required to reduce energy consumption, as well as associated costs and emissions. In this framework, Variable-base degree-days-based methods have been widely used for weather normalisation of energy statistics and energy monitoring for Measurement and Verification (M & V) purposes. The base temperature used to calculate degree-days is determined by building thermal characteristics, operation strategies, and occupant behaviour, and thus varies from building to building. In this paper, we develop a variable-base degrees days regression model, typically used for energy monitoring and M & V, using a “proxy” variable, the cost of energy services. The study’s goal is to assess the applicability of this type of model as a screening tool to analyse the impact of efficiency measures, as well as to understand the evolution of performance over time, and we test it on nine public schools in the Northern Italian city of Seregno. While not as accurate as M & V techniques, this regression-based approach can be a low-cost tool for tracking performance over time using cost data typically available in digital format and can work reasonably well with limited resolution, such as monthly data. The modelling methodology is simple, scalable and can be automated further, contributing to long-term techno-economic performance monitoring of building stock in the context of incremental built environment digitalization.

Research on Solar Power Generation Control System Based on 360 Degree Rotate Double-Motor

Aiming at the problems of low utilization rate of solar energy and poor anti-interference ability of tracking structure solar energy control system in fixed structure solar energy device, this paper designs a dual axis high-precision solar tracking system based on four quadrant rule. The system adopts two ways: automatic tracking and manual correction. The system uses four photoresistors as detection elements, uses the four quadrant principle to judge the tracking offset angle, and drives two-dimensional two axis stepper motor through STC89C52 processor to achieve the purpose of vertical angle, so as to ensure that the solar panel is always in the state of maximum light receiving surface; When the system is disturbed, it can be judged according to the change of the photosensitive resistance in the energy monitoring system, and the artificial correction can be realized by modulating the size of the divider resistance, which can basically achieve 360° Automatic rotation tracking. In addition, the energy monitoring system based on LabView is designed. Through the real system analysis, it can be concluded that the photoelectric energy conversion rate of the fixed solar device is increased by 32.4%.

Augmented Reality based Mobile Application for Energy Monitoring and IoT Device Control

IoT has become an integrated part of our lives changing ways in which we operate our everyday appliances. In addition to making our home appliances smart, it has become a common trend for companies to adopt industry 4.0, which uses various sensors to monitor the equipment, machinery, and the work environment. We often come across multiple brands which make smart appliances but each brand comes with its separate mobile application for the appliance's operation. This requires us to switch between Apps to control these appliances if we at all remember which App controls which appliance. We intend to solve these two major inconveniences by creating a single mobile application that can control all these appliances using Augmented Reality technology. All we have to do is point our camera at the appliance that we need to operate and the App will display control options in real-time AR. This paper produces five important contributions: 1) An AR-based mobile application to control IoT devices and monitor the environment. 2) Implementing the mobile application using Unity 3D engine and Vuforia SDK. 3) Integrating a commercially available IoT device with the mobile application. 4) Integrating custom-made hardware IoT device with mobile application. 5) Integrating this combination to make our industries and homes smarter Keywords:

Substantiation of the algorithm of information technology for energy monitoring of tractor engines

It is shown that it is necessary to control the energy indicators of automotive engines to ensure the operational efficiency of agricultural machinery in operational conditions. An algorithm for monitoring the energy indicators of the machine and tractor fleet of an agricultural enterprise is proposed, reflecting the main stages of obtaining, processing, storing and applying diagnostic information. Due to the timely assessment of the state of the equipment and the performance of the necessary maintenance, the efficiency of its work is increased.

Design And Development Of Real-Time Small Scale IoT Based Energy Monitoring System

This paper presents the digitization of small-scale energy monitoring systems based on IoT. The proposed energy monitoring system known as EMOSY eliminates the high-cost energy meter. EMOSY is designed to be portable and practical to use without modification of internal or external connection of appliances. EMOSY is developed by using a voltage detector circuit concept by amplifying the existence of electrostatic. This electrostatic reading sends to the database through Wi-Fi module ESP8266 integrated with Arduino NodeMCU. The web page is designed using Adobe Dreamweaver with HTML and PHP coding. In the proposed system, the user able to monitor the energy usage of each appliance and estimated billing time to time. Based on the result, the energy monitoring system successfully can detect the existence of electrostatic, and the webpage database can display the energy usage extended to the estimated electricity bill. The monitoring system is found to be useful to the residential, commercial, and industrial to monitor energy patterns, which is essential to facilitate energy conservation measures for minimizing energy usage.

Green switch: an IoT based energy monitoring system for mabini building in De La Salle Lipa

<p>Building energy management systems (BEMS) are critical tools for managing and controlling a facility's technical systems and services, such as lighting, ventilation, heating, and air conditioning, to ensure that the building operates at peak efficiency while decreasing energy waste. The Mabini Building at De La Salle Lipa has nearly a hundred rooms, 70 of which are used by college students for lecture and laboratory classes. From 7:30 a.m. to 9:00 p.m., these rooms are available. In a daily class schedule, air conditioning units and lights are used an average of 10 hours per day, while fans and power outlets are used an average of 5 hours. Even when no classes are being held, the aforementioned equipment is frequently left open in these rooms. The researchers created and constructed an IoT-based energy monitoring system to monitor and control the lights and outlets in a room. The system will also record the number of kilowatt-hours (kWh) consumed. The system employs NodeMCU, current, and voltage sensors, a Raspberry Pi 3, and the school's existing network to send and receive data from the server. The building administrator will use the collected data to give consumption statistics and reduce the carbon footprint.</p>