Smart Modulation for Control Systems with High Regulation Capabilities for Cooling Systems Optimisation and Carbon Footprint Reduction in Industry

Nowadays, every large enterprise is concerned about reducing CO2 emissions. Along with legislation, management, packaging, and transportation decisions, optimising the operation of automated systems in the industry is important. Overheating processes or large cooling systems of one machine during product assembly may seem minor but at the industry level it is quite significant. Either an optimisation of cooling systems or an intelligent machine control which will prevent heat strokes and allow the transition to passive cooling of the whole system is an important issue for improving machine tools efficiency and contributing therefore to CO2 reduction in the industry sector. This research is a transitional phase from the creation of a control system to solve the problems of resonance in the control of systems with parallel piezo kinematics, which were designed to automate the iterative process of non-circular drilling with a precise shape and the subsequent research on the implementation of smart control to optimise the cooling of industrial machines. The total dynamics of the example system in this research is unknown and consists of the dynamics of electrical converters, piezo kinematics, and mechanics. The control signal of this system is generated by the model of the system state with assumptions and simplifications in combination with machine learning techniques considering the previous errors of the transient characteristics with the possibility of re-drilling without damaging the workpiece and with possibility of further trainings to eliminate the iterative process in general. Algorithms for further training at different resonances with a drilling depth change for cylinders of internal combustion engines are offered. These algorithms are proposed for accurate transmission of the input signal amplitude even in resonant situations, power optimisation, increase the system efficiency, as well as reducing the carbon footprint when used in industry in specific applications.

A new multispectral photometer for monitoring aerosol microphysical, optical, and radiative properties

A new multispectral photometer, named CW193, was proposed in this study for monitoring aerosol microphysical, optical, and radiative properties. The instrument has a highly integrated design, smart control performance, and is composed of three parts (an optical head, a robotic drive platform, and a stents system). Because of its low maintenance requirements, this instrument is appropriate for the deployment in remote and unpopulated regions. Based on the synchronous measurements, the CW193 products was validated using reference data from the AERONET CE318 photometer. The results show that the raw digital counts from CW193 agree well the counts from AERONET (R2 > 0.97), with daily average triplets of around 1.2 % to 3.0 % for the ultraviolet band and less than 2.0 % for the visible and infrared bands. A good aerosol optical depth agreement (R > 0.99, 100 % within expected error) and root mean square error (RMSE) values ranging from 0.006 (for the 870 nm band) to 0.016 (for 440 nm the band) are obtained, with a relative mean bias (RMB) ranging from 0.922 to 1.112 and an aerosol optical depth bias within ±0.04. The maximum deviations for fine-mode particles varied from about 8.9 % to 77.6 %, whereas the variation for coarse-mode particles was about 13.1 % to 29.1 %. The deviation variations of the single scattering albedo were approximately 0.1–1.8 %, 0.6–1.9 %, 0.1–2.6 %, and 0.8–3.5 % for the 440 nm, 675 nm, 870 nm, and 1020 nm bands, respectively. For the aerosol direct radiative forcing, deviations of approximately 4.8–12.3 % was obtained at the Earth’s surface and 5.4–15.9 % for the top of the atmosphere. In addition, the water vapor retrievals showed a satisfactory accuracy, characterized by a high R value (~0.997), a small RMSE (~0.020), and good expected error distribution (100 % within expected error). The water vapor RMB was about 0.979 and the biases mostly varied within ±0.04, whereas the mean values were concentrated within ±0.02.

Development of Sustainable Indoor Air Quality for Air-Conditioning System Using Smart Control Techniques

Air-conditioning as a technical solution to protect inhabitants from excessive heat exposure creates the challenge of expanding indoor health effects. While air-conditioning has mostly been applied as an improvement to living conditions, health and environmental problems associated with its use frequently occurs. Therefore, this paper challenges and extends existing knowledge on sustainability related to the smart air-conditioning systems. The decrease of CO2 level in building requires an intelligent control system because energy utilisation has been legitimately connected with wellbeing and eventually to operational expenses. A building’s indoor environmental essential factors of comfort are IAQ, visual and thermal. Through an appropriate structured controller, the performance of indoor control system can be altogether improved. It merits creating innovative control techniques to optimise the indoor environment quality for air-conditioning system. The newly proposed backpropagation neural network was optimised using Matlab to control the CO2 level appropriately while carefully taking into account the performance of system controllers such as the stability, adaptability, speed response and overshoot. The controller of indoor environment was designed, and the proportional-integral-derivative control was utilised as a result of its suitability. The smart controllers were designed to regulate the parameters automatically to ensure the optimised control output. The indoor CO2 possesses an appropriate time constant and settling time of 2.1s and 27.3s, respectively. Therefore, utilising smart control techniques to exterminate various indoor health effects is expected to produce sustainable living conditions.

Dynamic Autonomous Identification and Intelligent Lighting of Moving Objects with Discomfort Glare Limitation

The importance of reducing discomfort glare during the dynamic development of high luminance LEDs is growing fast. Smart control systems also offer great opportunities to reduce electricity consumption for lighting purposes. Currently, dynamic “intelligent” lighting systems are a rapidly developing field. These systems, consisting of cameras and lighting units, such as moving heads or multimedia projectors, are powerful tools that provide a lot of opportunities. The aim of this research is to demonstrate the possibilities of using the projection light in dynamic lighting systems that enable the reduction of discomfort glare and the light pollution phenomenon. The proposed system allows darkening or reducing the luminance of some sensitive zones, such as the eyes or the head, in real-time. This paper explores the development of the markerless object tracking system. The precise identification of the position and geometry of objects and the human figure is used for dynamic lighting and mapping with any graphic content. Time measurements for downloading the depth maps, as well as for identifying the human body’s position and pose, have been performed. The analyses of the image transformation times have been carried out in relation to the resolution of the images displayed by the projector. The total computation time related to object detection and image display translates directly into the precision of fitting the projection image to a moving object and has been shown.

Empirical evaluation of energy profiles of thermally-efficient homes with smart energy systems and controls

Smart control technologies are beginning to be deployed in homes to optimise heating and alter the timing of domestic energy demand to enable residential demand side response (DSR). This paper presents before (baseline phase) and after (control phase) evaluation of the monitored indoor temperature and energy demand during the heating season in 10 new-build dwellings, each of which received a 5kWh electro-chemical battery and smart control to enable shifting of heating energy demand. The dwellings had air source heat pumps (ASHP) and 2kWp solar photovoltaic (PV) panels, and were located in a social housing estate in Barnsley, England. For eight dwellings, heat pump electricity use per heating degree day was found to decrease by 10% and narrow baseline peaks were suppressed during the control phase. Daily mean grid electricity import and heat pump electricity use in the peak period (4pm – 7pm) were measured as 4.0 kWh and 1.4 kWh during the control phase as compared to 3.8kWh and 1.3 kWh for the baseline phase. However the use of a flat tariff (single-rate) meant that battery charging-discharging capability was not fully utilised. Time-of-use tariff would further enhance cost savings associated with the change in the timing of energy demand.

Smart Control and Energy Efficiency in Irrigation Systems Using LoRaWAN

Irrigation installations in cities or agricultural operations use large amounts of water and electrical energy in their activity. Therefore, optimising these resources is essential nowadays. Wireless networks offer ideal support for such applications. The long-range wide-area network (LoRaWAN) used in this research offers a large coverage of up to 5 km, has low power consumption and does not need additional hardware such as repeaters or signal amplifiers. This research develops a control and monitoring system for irrigation systems. For this purpose, an irrigation algorithm is designed that uses rainfall probability data to regulate the irrigation of the installation. The algorithm is complemented by checking the sending and receiving of information in the LoRa network to reduce the loss of information packets. In addition, two temperature and humidity measurement devices for LoRaWAN (THMDLs) and an electrovalve control device for LoRaWAN (ECDLs) were developed. The hardware and software were also designed, and prototypes were built with the development of the electronic board. The wide coverage of the LoRaWAN allows the covering of small to large irrigation areas.