Internet of things based industrial environment monitoring and control: A design approach

In this research an internet of things (IoT) system is designed for the purpose of industrial environment monitoring and control. The system is mainly composed of control and sensor units. Control unit has the responsibility of managing the received data form the sensor unit and then executing the developed control algorithm based on the measured parameters.  NodeMCU development kit is used as the core of the control unit. The senor unit contains gas and temperature sensors utilized for measuring the temperature and concentration of toxic gases in the monitored space. A buzzer has also been embedded in the sensor unit for alerting the occupants acoustically in the danger situations. If the monitored temperature gets higher or lower than the set levels, the air conditioning system will be automatically operated. Similarly, the fan (ventilation) system will be operated if the level of toxic gases becomes high. A mobile application, based on Blynk platform, is then developed to enable the wireless monitoring and control of the environment by the in charge people. In addition to the automatic and wireless control the manual control capability is considered in the developed IoT system

How to control the Indoor Environmental Quality through the use of the Do-It-Yourself approach and new pervasive technologies

Abstract The article describes the results of the "Open-source Smart lamp" aimed at designing and developing a smart appliance that integrates a wireless communication system for building automation, following the maker movement philosophy. The device is able to get an overview of the potential of a nearable device equipped with a variety of sensors to broadcast digital data for the management and control of the Indoor Environmental Quality (IEQ) of the built environment. The Smart Lamp installed in a real office in order to test the reliability of the device in the management of the lighting and air quality levels

General Information About the Design of Smart Grids in Universities

Until recently, the dominant paradigm in the electrification consisted of universal service and its centralization, and for loor modern times think of the power grid of the future where a qualitative and radical leap is required because of the need to manage better energy resources, promote environmental protection and meet the increasingly demanding requirements of quality of service. A power distribution network becomes intelligent acquiring data, communicating, processing information and exercising control through a feedback that allows you to adjust to changes that may arise in actual operation. Ecuador aimed at energy efficiency through smart grids, which allow the dealer to maintain absolute monitoring of energy flow and the elements of the power grid. Thus, it is possible that service companies can efficiently manage their assets and the end user to manage consumption rationally, requiring to enhance the energy efficiency of power grids, one management timely and efficient energy

Monitoring System Analysis for Evaluating a Building’s Envelope Energy Performance through Estimation of Its Heat Loss Coefficient

The present article investigates the question of building energy monitoring systems used for data collection to estimate the Heat Loss Coefficient (HLC) with existing methods, in order to determine the Thermal Envelope Performance (TEP) of a building. The data requirements of HLC estimation methods are related to commonly used methods for fault detection, calibration, and supervision of energy monitoring systems in buildings. Based on an extended review of experimental tests to estimate the HLC undertaken since 1978, qualitative and quantitative analyses of the Monitoring and Controlling System (MCS) specifications have been carried out. The results show that no Fault Detection and Diagnosis (FDD) methods have been implemented in the reviewed literature. Furthermore, it was not possible to identify a trend of technology type used in sensors, hardware, software, and communication protocols, because a high percentage of the reviewed experimental tests do not specify the model, technical characteristics, or selection criteria of the implemented MCSs. Although most actual Building Automation Systems (BAS) may measure the required parameters, further research is still needed to ensure that these data are accurate enough to rigorously apply HLC estimation methods.This work was supported by: Spanish Economy and Competitiveness Ministry and European Regional Development Fund through the IMMOEN project: "Implementation of automated calibration and multiobjective optimization techniques applied to Building Energy Model simulations by means of monitored buildings". Project reference: ENE2015-65999-C2-2-R (MINECO/FEDER); European Commission through the A2PBEER project "Affordable and Adaptable Public Buildings through Energy Efficient Retrofitting". Grant agreement No.: 609060; Laboratory for the Quality Control of Buildings (LCCE) of the Basque Government; University of the Basque Country (UPV/EHU). Framework agreement: Euro-regional Campus of Excellence within the context of their respective excellence projects, Euskampus and IdEx Bordeaux. Funder reference: PIFBUR 16/26

An intelligent energy management system for educational buildings

There is a wide variation in the energy consumption between different educational institutions due to the adoption of different management strategies and different levels of occupants’ environmental understanding. The presence of large amounts of information and communication technology (ICT) equipment and heating, ventilation, and air conditioning (HVAC) system causes a major consumption of energy in higher education institution (HEI) buildings. The main objective of this research is to investigate the use of ICT to optimize the energy consumption in HEI buildings and reduce carbon dioxide (CO 2 ) emission. The first phase of the system has been implemented at King Saud University to measure energy consumption through sensors that read energy consumption of electrical appliances and devices every 10 seconds. The analysis of collected data allows us to develop and employ energy saving strategies that lead to a reduction in total energy consumption. Our preliminary results show that up to 17% of energy consumption can be reduced by simply dealing with standby energy loss of labs’ computers. The novelty of this research comes from the use of a functional database approach to deal with high volume of data and query performance and the incorporation of a timetabling system in energy management system