Smart Control System Research Articles

Remote Monitoring and Smart Control System for Greenhouse Environmental and Automation Irrigations Based on WSNs and GSM Module

This paper depicts the automatic irrigation and environmental monitoring inside the greenhouse based on WSNs (Wireless Sensor Networks) and GSM Module. The system is able to collect information about key environmental parameters, such as temperature, relative humidity, Water level within irrigation water tanks, light ratio, CO2 dosage and soil dryness within the greenhouse. Analog signals from different sensors are converted to digital values by taking advantage of the ability of GSM (Global System for Mobile Communications) to convert analog signal to digital without the use of microcontroller. This information is transmitted wirelessly to the central computer to be processed and decided on by way of applying a simple fuzzy input system to send appropriate digital commands via the digital outputs of the system to regulate the glass house parameters within acceptable limits. The collected data and control commands that are applied in the database are stored to be analyzed for purposes of improving Agriculture.

Development and verification of a smart remote control system for home appliances

People usually adopt a specific remote controller to monitor each home appliance, which is really inconvenient. In order to integrate different remote control functions into one software Application (App) on the smartphone, a smart remote control system is developed using the following two steps. The first step is to transform the designed operational flowchart of a smart remote control system into the Petri net model. It can avoid the potential hazards or vulnerabilities remained in the logically incorrect systems. Furthermore, through the deadlock verification, a deadlock can be prevented from the system design. The second step is to control home appliances remotely by using a smartphone with Bluetooth or WiFi network and sending commands to the infrared (IR) equipment. Finally, the experimental results have indicated that our daily life will become more convenient and safer when using a smartphone to control the home appliances remotely.

Development of Wireless Control System for Smart Street Lighting using ESP8266

In this paper, we report a smart street lighting control system using the ESP8266 which is a low-cost Wi-Fi chip with full TCP/IP stack and microcontroller capability. Our system is equipped with a web server developed in HTML code. Hence, our smart street lighting system can be controlled wirelessly to turn ON or turn OFF, and it can be monitored its environmental condition (i.e., temperature and humidity around the system). All sensors used in this system are pure digitally-outputted sensor: DHT11 to monitor the ambient temperature and humidity and BH1750 to adjust the street light intensity automatically. The dimming technique was applied in the control system by using Pulse Width Modulation (PWM). The system was divided into two main parts: Gateway and Node in which these two parts employ the ESP8266. The Gateway as a coordinator will send a message to the node as an end device (in this work, the streetlight act as a Node). Later, the node will send the ACK to the Gateway. As results, each node can send a message to other nodes.

Design of a motorised plasma delivery system for ultra-precision large optical fabrication

A unique plasma figuring (PF) process was created and demonstrated at Cranfield University for manufacturing extremely large telescopes. The atmospheric pressure processing is faster and more cost-effective than other finishing processes; thus, providing an important alternative for large optical surfaces. The industrial scale manufacturing of thousands of ultra-precision metre-scale optics requires a robust PF machine: this requirement is achieved by making the plasma delivery system (PDS) performance repeatable. In this study, a dedicated PDS for large optical manufacturing was proposed to meet the industrial requirement. The PDS is based on an L-type radiofrequency (RF) network, a power supply, and an inductively coupled plasma torch. However, the complexities of these technologies require an in depth understanding of the integrated components that from the PDS. A smart control system for the modified PDS was created. This novel control system aims to make the characterization process deterministic: by automating the tuning of critical electrical components in the RF network, which is achieved by the use of in-line metrology. This paper describes the main design aspects. The PDS was tested with a good correlation between capacitance and RF frequencies. The robust PDS design enables a stable discharge of plasma with a low deviation of RF signals during the total 15 hours’ test.

Autonomous energy management system with self-healing capabilities for green buildings (microgrids)

Nowadays, distributed energy sources are widely used to supply demand in micro grids (MGs) especially in the green buildings. Despite increasing number of intermittent distributed energy resources, MGs have essential influence on decreasing use of conventional generation, but it give rise to new challenges in terms of energy management, stability and reliability of system. Multi-agent systems (MASs) as distributed smart units have been widely used recently. However, control and implementation of these smart structures enhance existing challenges because these units need a framework that, at first, guarantees operation of MASs and then insures management in generation and demand side. This paper presents a smart control and energy management of a DC microgrid that split the demand among several generators. An energy management system (EMS) based on multi-agent system (MAS) controller is developed to manage energy, control the voltage and create balance between supply and demand in the system with the aim of supporting reliability characteristic. In the proposed approach, a self-healing hierarchical algorithm is implemented to control interaction of agents and also guarantees reliability of smart control system under faults. Theoretical analysis and simulation results for a practical model demonstrate that the proposed technique provides a robust and stable control of a microgrid.

Research and Application of Smart Lock Safety Management and Control System

The total number of switch stations and distribution stations in the distribution network has increased year by year; overhead lines have been gradually cabled to the ground; the number of ring network cabinets and box-type transformers has increased rapidly. The distribution network equipment has the characteristics of “small, large quantity, and decentralized”, and it is difficult to manage. For a long time, problems such as theft, unauthorized unpacking operations, and unauthorized private operations have been troubling distribution network operation managers, affecting the safe and stable operation of the distribution network and reliable external power supply. The intelligent lock safety management and control system proposed in this paper is based on the actual situation of the power distribution network, and replaces the original mechanical lock with an intelligent lock. The system implements real-time effective management and control of the production operation process and status of power distribution equipment through the “authorized unlocking” of the handheld terminal. At the same time, it implements information and visual management of equipment, staff and related information, so that distribution network managers can play the role of “master”. This system can manage and control the power distribution equipment, and improve the operation and management level of the power distribution network.

Smart Agricultural activities Monitoring and Control system using an Internet of Things

Smart Agricultural activities Monitoring and Control system using an Internet of Things

Gas micro-turbines with high-speed electric generators for local smart energy systems

At present, the share of energy collected from renewable resources and low-power units is growing, and the generation becomes distributed, having many facilities that operate in co-generation mode. That is why the construction of an energy system with distributed heterogeneous sources and the improvement of its efficiency have become widely discussed issues. This paper proposes a solution of a local smart energy systemfortheTechnoEcoPark, a sciencepark of Rostov State Transport University, Rostov, Russia. The solution aims to integrate the distributed generation facilities, including environmentally friendly renewable resources, grid infrastructure and consumers with controllable and uncontrollable load. Theapproachtothe problem is the application of a smart control systemthatmanagesgeneration, distribution and consumptionof energy in a mini-CHP-based autonomous energy system. Such smart control systems reveal the trends of optimal energydistribution in a autonomousenergysystem. The study substantiates that installation of an in-house mini-CHP can solve the task of supplying heat and powertotheTechnoEcoPark. The important advantage of the solution is a significant reduction of expenses on energy consumption as the generation costs less compared to the grid tariffs. The proposed energy supply system of the TechnoEcoPark exemplifies the integration of heterogeneous heat and power sources and consumers into a commonnetwork. The paper outlines the mechanisms of the energy system efficiency improvement. These mechanisms make it possible to provide heat and power supply services to consumers and to return the generated power into the centralized grid. The materials of the paper can be of use to the specialists and researchers who are interested in generation and distribution of energy in autonomous systems.

Smart management and control system for liquid radioactive waste in hospitals using neural network techniques

In tertiary hospitals where the nuclear medicine services have been introduced, the radioactive materials used in diagnosis and / or treatment need to be handled. The hospital design and medical planning should consider such these materials and their policy for treatment. The nuclear wastes have been divided into solid and liquid based on the used materials and for their half-life times which start from few minutes till reaching years. In our study, the most common radioactive liquid materials (wastes) have been treated by smart system. The system will detect the material of the waste via nuclear sensors and based on its HLT (activities), it will be distributed in two shielded storage tanks classified based on capacity then to the sewage treatment plant (STP) of the hospital after keeping for required times. The location and capacity of these tanks together with their monitoring and control system should be considered in design stage which determines the treatment processes. By applying our proposed technique on two hospitals, the results have reduced the storage tank capacity by 87% (reduction) and space area leading to cost reduction by 72% keeping the maximum level of safety.

Angle-sensitive dynamic optical modulation based on Huygens metasurfaces

Recently, dynamic metasurfaces have attracted significant attention due to their ability to actively control electromagnetic waves upon external tunings. The realization of high performance dynamic metasurfaces-based devices remains a great challenge due to very limited modulation depths. Here based on the Huygens metasurfaces, the high efficient active control of transmitted wave was realized by the combination of dielectric resonators and a phase transition material (vanadium dioxide, VO2). At Huygens-mode wavelength, the metasurface demonstrated 82.5% transmission and ~80% modulation depth. Besides, it exhibits angle-sensitivity and polarization-independence under normal incidence. The proposed metasurface provides a new way for optical switching, filtering, passive temperature control modulation, which would possess broad application prospects for integrated optical devices, near-infrared photodetection, and smart temperature control systems.

Sustainable Smart City Building Construction Methods

In a global world, the human population invariably increases while resources gradually decrease as cities and towns constantly consume resources to satisfy their needs and requirements. At this point, it is very necessary to focus on making these urban areas more sustainable and greener. The need for some advanced and automated systems improves the situation, which leads to the innovation of smart cities. Smart city is the concept that helps in developing sustainable cities via optimized resource utilization methods. In smart city development, various sensing technologies can be used that can sense and utilize natural resources in better ways, like storing rainwater to use afterward, intelligent and smart control system, smart infrastructure monitoring system, smart healthcare system, smart transportation system, and smart system for energy consumption and generation by various facilities. To make the city smart and sustainable with efficient energy consumption, we propose renewable solar and wind energy-enabled hybrid heating and cooling HVAC-DHW (heating, ventilation, and air conditioning-Domestic Hot Water) system in which energy consumption is evaluated using optimized NARX-ANN and fuzzy controller based on user needs, dynamic behavior of the atmospheric environment, and spatial distribution of energy supply. To achieve the proposed goal, first, via sensor, heating and cooling effect of environment and building is sensed and these sensed inputs are then fed into deep-learning-based NARX-ANN that forecast internal building temperature. This forecasted temperature is fed into a fuzzy controller for optimizing output based on user demand. This processed information leads to energy distribution based on their requirement using a smart energy sensing system. Based on the experimentation result and performance analysis, it was found that the proposed system is more robust and has a high control response in comparison to the existing systems with minimum energy consumption. The analytical results support the feasibility of the proposed framework architecture to facilitate energy conserving in smart city buildings.

Theoretical Assessment of Sustainability Principles for Renewable Smart Air-ConditioningTheoretical Assessment of Sustainability Principles for Renewable Smart Air-Conditioning

Upon an improvement in the quality of life, air-conditioning has generally been applied. Nevertheless, environmental and health issues related with the use of air-conditioning occurs more often. Therefore, this paper aims to theoretically assess the principles of sustainability to achieve sustainability for renewable smart air-conditioning. Not only with consideration to the geometry (i.e. system mechanisms and components), fuzzy logic control and proportional-integral-derivative that such studies drawn particular attention to, but with concerns to a matter which has been previously ignored. That is with consideration to the potential which the renewable-based options, advanced smart control technique and profitability measures of air-conditioning reinforces the three pillars of sustainability, and their sustainable indicators as context-specific transformations have, to not only eradicate indoor health effects, lower the levels of energy consumption and rate of carbon emissions, but to uncover the significance of and particular contribution renewables and smart control opportunities makes to the sustainability of the system. In meeting this aim and demonstrating the sustainability of the theoretical framework, this paper reveals renewable and smart control system as the fundamental key components of the air-conditioning as it promotes to reduce levels of energy consumption and lower carbon emissions, vis-à-vis establish a comfortable and healthy indoor environment as an exercise in the sustainable theoretical framework whose status as renewable smart air-conditioning not only tackle poor indoor air quality but also combat global warming and climate change.

Design and Development of Automatic Smart Control System for Water Sprinkling and Ventilation

Design and Development of Automatic Smart Control System for Water Sprinkling and Ventilation

Smart home energy strategy based on human behaviour patterns for transformative computing

Transformative computing in the fourth-generation industrialization, receives all signals and all sequences from sensing devices under artificial intelligence in wireless networking. Then the system has to combine them and make a useful information for human. In an industrial building or in a home, many electronic devices would be using and they make various energy signals and sequences. The devices can find out the energy wastage in the absence of a smart energy management system to monitor the energy flow, and it causes a blackout. Once the energy flow is analysed, it is possible to realize the special-time or the rush-time, which will require a large amount of energy. Because the existing systems have no monitor to see the energy flow, a large amount of energy can be wasted. To distribute the energy efficiently, a smart energy management system should have the necessary special functions that can monitor the energy flow. Following the analysis result, the system can create a special strategy to plan energy distribution. In this study, the smart energy management system defines a special strategy based on the analysis result of the consumed energy by arranging more or less usage of energy. Moreover, the system can decrease the energy supply to idle devices and the connected extra devices by analysing how many IoT will be used in a service. This smart control system can detect human behaviour when they move and turn in activation automatically, so finally, the system can use the energy efficiently.

An In-Depth Analysis of IoT Security Requirements, Challenges, and Their Countermeasures via Software-Defined Security

Internet of Things (IoT) is transforming everyone's life by providing features, such as controlling and monitoring of the connected smart objects. IoT applications range over a broad spectrum of services including smart cities, homes, cars, manufacturing, e-healthcare, smart control system, transportation, wearables, farming, and much more. The adoption of these devices is growing exponentially, that has resulted in generation of a substantial amount of data for processing and analyzing. Thus, besides bringing ease to the human lives, these devices are susceptible to different threats and security challenges, which do not only worry the users for adopting it in sensitive environments, such as e-health, smart home, etc., but also pose hazards for the advancement of IoT in coming days. This article thoroughly reviews the threats, security requirements, challenges, and the attack vectors pertinent to IoT networks. Based on the gap analysis, a novel paradigm that combines a network-based deployment of IoT architecture through software-defined networking (SDN) is proposed. This article presents an overview of the SDN along with a thorough discussion on SDN-based IoT deployment models, i.e., centralized and decentralized. We further elaborated SDN-based IoT security solutions to present a comprehensive overview of the software-defined security (SDSec) technology. Furthermore, based on the literature, core issues are highlighted that are the main hurdles in unifying all IoT stakeholders on one platform and few findings that emphases on a network-based security solution for IoT paradigm. Finally, some future research directions of SDN-based IoT security technologies are discussed.

SMART SPRAYER DISINSFEKTAN BERBASIS MIKROKONTROLER ATMEGA328

During the pandemic covid 19 we are experiencing at this time, various technological innovations are created as the first step in breaking the chain of corona virus. One way that can be implemented in breaking the covid pandemic chain of 19, especially in public areas is by spraying a disinfectant liquid that can be done continuously. Optimization of spraying disinfectant liquid can be done by utilizing technology that is able to work automatically. This research makes a disinfectant sprayer chamber as a technological innovation. Automation of disinfectant sprayers can be done by utilizing the ATemega328 microcontroller as an automatic machine to activate the sprayer pump based on the detection of objects that are around it with the help of an ultrasonic sensor. Determination of the distance reading of the object greatly determines the performance of the ultrasonic sensor in providing input to the microcontroller. The smart sprayer system is capable of activating a 12Volt DC pump with a voltage of 5 amperes. This smart sprayer disinfectant control system can be applied to the gate or hallway at the center of the crowd.

Machine learning for predictive scheduling and resource allocation in large scale manufacturing systems

The digitalization processes in manufacturing enterprises and the integration of increasingly smart shop floor devices and software control systems caused an explosion in the data points available in Manufacturing Execution Systems. The degree in which enterprises can capture value from big data processing and extract useful insights represents a differentiating factor in developing controls that optimize production and protect resources. Machine learning and Big Data technologies have gained increased traction being adopted in some critical areas of planning and control. Cloud manufacturing allows using these technologies in real time, lowering the cost of implementing and deployment. In this context, the paper offers a machine learning approach for reality awareness and optimization in cloud.Specifically, the paper focuses on predictive production planning (operation scheduling, resource allocation) and predictive maintenance. The main contribution of this research consists in developing a hybrid control solution that uses Big Data techniques and machine learning algorithms to process in real time information streams in large scale manufacturing systems, focusing on energy consumptions that are aggregated at various layers. The control architecture is distributed at the edge of the shop floor for data collecting and format transformation, and then centralized at the cloud computing platform for data aggregation, machine learning and intelligent decisions. The information is aggregated in logical streams and consolidated based on relevant metadata; a neural network is trained and used to determine possible anomalies or variations relative to the normal patterns of energy consumption at each layer. This novel approach allows for accurate forecasting of energy consumption patterns during production by using Long Short-term Memory neural networks and deep learning in real time to re-assign resources (for batch cost optimization) and detect anomalies (for robustness) based on predicted energy data.

Microfluidic Synthesis of Luminescent and Plasmonic Nanoparticles: Fast, Efficient, and Data‐Rich

AbstractMicrofluidic approaches to nanomaterial synthesis provide an effective means of making high quality products, with exquisite control over electronic, optical, and structural properties. Furthermore, microfluidic reactors integrating analytics and real‐time reaction control have recently emerged as powerful tools in automating materials exploration and reaction parameter mapping, with a rapidity and efficiency that is inaccessible to traditional flask‐based methods. Herein, the recent innovations in the microfluidic synthesis of photonic nanoparticles, whose varied luminescent and plasmonic properties have found great application in the biomedical and optoelectronic sciences, are presented. Special attention is placed on the achievements and promise of microfluidic approaches in automated multidimensional reaction parameter screening employing in situ optical characterization. In an extended outlook, the future of the field is explored, looking toward the integration of smart control systems and machine learning algorithms, and demonstrating how maximal positive impact can be achieved. Far from degrading or replacing the ingenuity of the experimentalist, these tools will provide new powers of exploration, augmenting the discovery process. Further, through automation and miniaturization, it is expected that such approaches will fulfill the moral imperative of maximizing the benefit derived from the natural resources consumed in conducting research.

Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications

Many companies are struggling to manage their production systems due to increasing market uncertainty. While emerging ‘smart’ technologies such as the internet of things, machine learning, and cloud computing have been touted as having the potential to transform production management, the realities of their adoption and use have been much more challenging than anticipated. In this paper, we explore these challenges and present a conceptual model, a use-case matrix and a product–process framework for a smart production planning and control (smart PPC) system and illustrate the use of these artefacts through four case companies. The presented model adopts an incremental approach that companies with limited resources could employ in improving their PPC process in the context of industry 4.0 and sustainability. The results reveal that while make-to-order companies are more likely to derive greater benefits from a smart product strategy, make-to-stock companies are more likely to derive the most benefit from pursuing a smart process strategy, and consequently a smart PPC solution.

Smart sensor based distillation for fractionating citronella oil: current research challenges

Citronella oil is one of the essential oils derived from the leaves and stem of lemongrass (Cymbopogon nardus). At present, most of the lemongrass oil industry in Indonesia is still in the form of upstream industries which only provide crude purified oils with low purity for export with a fairly low sales value. Technology in improving the purity of citronella oil needs innovation in following the development of the industrial revolution 4.0. This article presents an overview of the research opportunities in the development of distillation for fractionating citronella oil referring to automation of optimization processes in the vacuum fractional distillation accompanied by inspection of the quality of essential oil isolation run in the line process based on smart sensors integrated in a computer program. The combination technique of quality control of essential oils in line process system combined with the optimization technique of the vacuum fractional distillation process has not been studied by advanced researchers. Therefore, this study has a state of the art process engineering and smart sensor-based quality control systems that can be developed for strengthening the Indonesian citronella oil industry.