Reduce Power Usage Research Articles

Reliable Data Transmission in Underwater Wireless Sensor Networks Using a Cluster-Based Routing Protocol Endorsed by Member Nodes

Considering Underwater Wireless Sensor Networks (UWSNs) have limited power resources (low bandwidth, long propagation delays, and non-rechargeable batteries), it is critical that they develop solutions to reduce power usage. Clustering is one solution because it not only saves energy consumption but also improves scalability and data integrity. The design of UWSNs is vital to the development of clustering algorithms. The limited energy of sensor nodes, narrow transmission bandwidth, and unpredictable topology of mobile Underwater Acoustic Wireless Sensor Networks (UAWSNs) make it challenging to build an effective and dependable underwater communication network. Despite its success in data dependability, the acoustic underwater communication channel consumes the greatest energy at a node. Recharging and replacing a submerged node’s battery could be prohibitively expensive. We propose a network architecture called Member Nodes Supported Cluster-Based Routing Protocol (MNS-CBRP) to achieve consistent information transfer speeds by using the network’s member nodes. As a result, we use clusters, which are produced by dividing the network’s space into many minute circular sections. Following that, a Cluster Head (CH) node is chosen for each circle. Despite the fact that the source nodes are randomly spread, all of the cluster heads are linked to the circle’s focal point. It is the responsibility of the MNS-CBRP source nodes to communicate the discovered information to the CH. The discovered data will then be sent to the CH that follows it, and so on, until all data packets have been transferred to the surface sinks. We tested our techniques thoroughly using QualNet Simulator to determine their viability.

Performance of refrigeration system using Al2O3, CuO and TiO2 nano-enhanced refrigerants: A review

Refrigeration is an ever-growing field where we are always looking for environmentally cleaner, more efficient and more usable ways to enhance and discover substances and materials for refrigeration. Nanoparticles are one way to achieve this goal of great energy savings and resulting emissions reductions. The refrigeration interaction becomes more proficient and protected as contrasted with the past in the environment. The key objective of this article is to review the performance of refrigeration systems with Al2O3, CuO and TiO2 nano-enhanced refrigerants. The Review revealed that when the TiO2 nanoparticle was introduced to the R134a refrigerant, the maximum enhancement in coefficient of performance is 18.75%. On the other hand, Al2O3/R134a offers a 27% reduction in power usage when compared to traditional fluids. Compared to R134a/CuO, the Al2O3/R134a nano-refrigerant offers energy savings that are more than five times greater and 80% more effective.

Lightweight compression with encryption based on asymmetric numeral systems

Data compression combined with effective encryption is a common requirement of data storage and transmission. Low cost of these operations is often a high priority in order to increase transmission speed and reduce power usage. This requirement is crucial for battery-powered devices with limited resources, such as autonomous remote sensors or implants. Well-known and popular encryption techniques are frequently too expensive. This problem is on the increase as machine-to-machine communication and the Internet of Things are becoming a reality. Therefore, there is growing demand for finding trade-offs between security, cost and performance in lightweight cryptography. This article discusses Asymmetric Numeral Systems -- an innovative approach to entropy coding which can be used for compression with encryption. It provides compression ratio comparable with arithmetic coding at similar speed as Huffman coding, hence, this coding is starting to replace them in new compressors. Additionally, by perturbing its coding tables, the Asymmetric Numeral System makes it possible to simultaneously encrypt the encoded message at nearly no additional cost. The article introduces this approach and analyzes its security level. The basic application is reducing the number of rounds of some cipher used on ANS-compressed data, or completely removing additional encryption layer if reaching a satisfactory protection level.

Constructing a (fair) load-reduction emergency demand response program: A fee-and-rebate pricing mechanism

Emergent power shortages and power outages cause enormous economic losses. Special fees and rebates at times when the operating reserve is below standard are among the most popular mechanisms for driving demand response, i.e., a spontaneous reduction in power usage, to help alleviate peak loads. However, a rebate which is uniform for all users usually under- or over-estimates companies’ incentive to respond, as product profitability and the cost of manufacturing vary from one company to another. As a result, the power provider either fails to sufficiently reduce the load during a period of scarcity of electric power or unduly sacrifices profits to pay an excessive rebate. This study presents a Stackelberg game-theoretic model that determines discriminative rebates and scarcity pricing of electricity, thereby capturing incentives of different industrial users to respond rationally and reduce their power usage. The model can be used to assess the current pricing and rebate structure and has the potential to serve as the fee-and-rebate mechanism in an Emergency Demand Response Program. A case study is used to simulate a game between the Taiwan Power Company and four classes of heterogeneous industrial customers who are willing to cooperate with the power provider on implementation of an Emergency Demand Response Program. The results show that the profits of the participants are higher than the profits of the non-participants. Moreover, a high-value-added and non-interruptible manufacturing class should be paid higher rebate.

A low-power communication scheme for wireless, 1000 channel brain–machine interfaces

Objective. Brain–machine interfaces (BMIs) have the potential to restore motor function but are currently limited by electrode count and long-term recording stability. These challenges may be solved through the use of free-floating ‘motes’ which wirelessly transmit recorded neural signals, if power consumption can be kept within safe levels when scaling to thousands of motes. Here, we evaluated a pulse-interval modulation (PIM) communication scheme for infrared (IR)-based motes that aims to reduce the wireless data rate and system power consumption. Approach. To test PIM’s ability to efficiently communicate neural information, we simulated the communication scheme in a real-time closed-loop BMI with non-human primates. Additionally, we performed circuit simulations of an IR-based 1000-mote system to calculate communication accuracy and total power consumption. Main results. We found that PIM at 1 kb/s per channel maintained strong correlations with true firing rate and matched online BMI performance of a traditional wired system. Closed-loop BMI tests suggest that lags as small as 30 ms can have significant performance effects. Finally, unlike other IR communication schemes, PIM is feasible in terms of power, and neural data can accurately be recovered on a receiver using 3 mW for 1000 channels. Significance. These results suggest that PIM-based communication could significantly reduce power usage of wireless motes to enable higher channel-counts for high-performance BMIs.

Modelling of energy and related parameters during milling: Review and discussions

Manufacturing is one of the key activities used to assess any industrialized countries economic strength. Machining is a well-liked manufacturing process and milling is a widespread metal removing process for the production of complex profile components. High energy consumption during the machining process results in higher energy usage, more toxic pollution and higher energy prices. Hence for cost reduction and to ensure economic in addition to environmental sustainability, reducing power usage is a significant factor. Along with the amount of consumption in energy reduced, the improvement in energy efficiency and power factor are also important factors to improve sustainability in this segment. The energy consumption, energy efficiency and power factor during machining are dependent on different process parameters like feed rate, geometry of the cutter, cutting speed, material of the cutter, depth of cut, material of the workpiece and cutting environment. So, that choice of the optimum values of these process parameters is one of the key approaches to improve the machining performance. The literature on energy modelling and associated parameters using theoretical, empirical and experimental techniques for milling operations is discussed in this article. It illustrates the approach used for the model and the significance of these works. Theoretical and empirical models are initially examined, accompanied by discussions on experimental models developed using design of experiments. The paper seeks to point out the recent developments in the modelling of energy and related parameters for milling operations and also to discover the regions that needs to be considered for future studies.

Design of cost-effective real time tremor alerting system for patients of neurodegenerative diseases

In recent years, many people are affected by neurodegenerative disorders like Alzheimer, Parkinson, motor neuron disease, and Chorea. Brain function loss, movement problems and typically cognitive impairments occur from their influence on the central nervous system. In this situation, early symptom monitoring and assessment are essential for enhancing the tremor patient life. Here, we propose embedded system development, for early alerting of tremors by integrating heart rate and MEMS sensors. In the created system, a collection of different four sensors are linked to a development board. This device can track the geographical location of Alzheimer's patients and detect tremor/movement, as well as accidental falls. Using GSM connectivity, a remote administrator may collect data from the development board. A data compression method is constructed directly on board to improve data transmission efficiency and reduce power usage.

Automated Humidity Control System for Neonatal Incubator

Premature neonates are nursed in closed incubators to prevent transcutaneous water loss, dehydration, and excessive body cooling. These issues have serious risks that need to be eliminated by controlling the air’s relative humidity (RH) in the incubator. This paper aims to implement a closed-loop control system that maintains desired RH levels inside the incubator with an acceptable settling time and percentage. Designing the prototype is actuator-process-sensor based, and the implementation was in two main phases. First, building the incubator, which involved assembling the incubation space and the humidifier using a readily available ultrasonic piezoelectric transducer. Second, designing the control algorithm which is based on the ON/OFF algorithm with four levels of ON Humidification power. Finally, the results taken are the control system responses to a step input of desired values of relative humidity based on clinical guidance. Response results showed a maximum steady-state error of 2.5 and a minimum settling time of 0.8 min. The results indicate that the control system is fast and stable which meets the desired requirements. The designed control system is beneficial in reducing power usage and creating a safe humidification method for the infant.

Multi-RAT Orchestration Method for Heterogeneous Wireless Networks

Currently, energy efficiency (EE) of wireless communication is essential where many wireless networks with different Radio Access Technologies (RATs) coexist together. The RATs can be effectively selected and managed on a higher level to achieve maximum EE and save energy, e.g., save batteries. The approach to wireless traffic steering in mobile networks with a proof-of-concept solution is presented in this paper, owing to the developed high-level multi-RAT (multi-Radio Access Technology) heterogonous network orchestration approach. Based on the high-level network orchestrator, which traces network indicators, it is possible to decrease the user mobile terminal energy consumption, keeping traffic speed at an adequate level. The solution discussed was implemented in an experimental testbed with Software Defined Radio transmission systems. Downlink and uplink data links were toggled among different RATs according to the decisions that were taken by the end-to-end multi-RAT orchestrator based on the received proper network traffic-related indicators. The authors focused on finding an adequate algorithm that allowed for reduced power usage in the user terminal and made the attempt to verify how to reach the power reduction without introducing RAT-specific rules. The results showed that the proposed orchestration EE reduction was observed (from 11% to 42% for two different scenarios) in relation to the single LTE network deployment. The orchestration compared to the Wi-Fi network does not provide EE gain (−7% and 0%, respectively), but allows the user to achieve a higher data rate (23% and 39% gain, respectively), thus keeping the energy efficiency at almost the same level.

Multi-element full-duplex FSO transceiver design using optimum tiling

With ever-growing demand of high-speed mobile data and in vision of smart cities, optical wireless, a.k.a. free-space optical (FSO), communication deem to be a critical technology due to its significantly faster data transfer rate, higher security, lower costs, and reduced power usage. These beneficial effects have led to interest in exploring FSO technologies for mobile platforms such as drone-based cell tower to provide Internet services to remote areas, or even for wireless communications on the ground with jammed radio channels as in battlefields. Direct line-of-sight (LOS) is required to establish secure directional FSO communication (FSOC) links which are highly susceptible to random and erratic movements of the mobile nodes as well as the turbulence in the free-space medium. The performance of FSOC links can be improved by designing multi-element tiling of the laser-based transceivers which is capable of in-band full-duplex (IBFD) communication. In this work, we propose a genetic algorithm framework to explore optimized multi-element FSO transceiver tiling patterns to ensure maximal signal-to-interference and noise ratio (SINR) and minimize the effects of vibration of the mobile platform and atmospheric turbulence.

Performance analysis of desiccant dehumidifier with different channel geometry using CFD

Traditional cooling systems based on vapor compression are ineffective in humid climates due to their inability to remove moisture below the dew point of the conditioned air, which necessitates additional effort in the form of electrical power supply to run vapor compressors. A solid desiccant cooling system reduces power usage while simultaneously providing fresh and clean air. It is important to examine and analyse the performance of desiccant dehumidifiers that will help to develop more efficient cooling system. A Computational Fluid Dynamic (CFD) simulation predicts the numerical performance of the solid desiccant wheel while dehumidifying moist room air during dehumidification. The aim of this study is to conduct performance study of different desiccant wheel channel geometries like triangular, square, hexagonal, sinusoidal-1 and sinusoidal-2 using simulation carried out with the help of CFD for various operating performance input parameters like supply air temperature, velocity, pressure and humidity of air. The CFD simulation technique evaluates all channel geometry shapes and identifies the most effective geometry among them that provide the most efficient dehumidification. During simulation, the operating parameters of supply process air were considered as 25°C temperature and 50 % (RH) in the case of a recirculation mode. Similarly, in the case of ventilation mode, for supply of process air, two transient climatic conditions have been selected for the city of Dahod, INDIA, as outdoor Condition-I 29°C with 83 % RH and outdoor condition II 35.8°C with 60.5 % RH for the supply of process air. The simulation results estimate the moisture removal capacity for different geometries under various operating conditions. It is found that the sinusoidal types of geometry provide substantial drop in the relative humidity up to 80.01 % with the average temperature raised by 38.98 % of supply air and provide the most effective dehumidification of the supply process air. As a result, CFD simulation techniques aid in the saving time which spent on rigorous experimentation and avoiding the cost of critical construction for various shapes of geometry.

Energy-saving of building envelope using passive PCM technique: A case study of Kuwait City climate conditions

In the Kuwaiti climate region, the residential sector accounts for 64% of electricity consumption. Due to the hot climate for this region, the share of cooling power usage to meet the ventilation requirements in residential buildings is significant. One of the effective methods to reduce power usage is to reduce heat gain. In this numerical study, taking into account the Kuwait City climate region, a PCM layer with a thickness of 20 mm was added to the vertical walls as well as the roof to examine the heat exchange reduction. In the warmeth month (July) by adding PCM of RT-42 to the roof, the heat gain reduced by 15.37%, while this figure for vertical walls was approximately 13.78% which implies that the geographical direction has not considerable effects on PCM usefulness. To investigate the effects of melting temperature on heat gain, three PCMs of RT-31 (phase change temperature of 27–33 °C), RT-35 (29–36 °C and RT-42 (38–43 °C) were examined. Annual calculations showed that RT-31 effectiveness was better than other PCMs so that loading RT-31 into vertical walls + roof resulted in energy saving as well as CO2 saving by 481kWhm2.year and 198.65kgCO2m2.year, respectively.

Implementation of IoT to reduce the use of electrical energy

Electricity consumption in Indonesia continues to increase by an average of 6.8% per year. IoT in 4.0 industry can be used to help community in reducing energy consumtion, including electricity, by implementing smart home sensor and actuator in IoT can be used to control the electricity consumtion automatically. This research has an objective to design and apply smart home that can reduce the electricity consumtion. The Smart Home device is an Arduino ESP8266 NodeMCU microcontroller equipped with a PIR sensor, DHT11 sensor and relay. This system is connected to the website as a controlling system. The smart home can also reduce power usage on street light by 7,524.91 watts (59.72%), living room light by 1,500 watts (50%), kitchen light by 2699,94 watts (75 )%), the main room lamp is 1259.98 watts (50%). Smart home system with a timer for one month can reduce power usage by 12,984.83 watts (12.01%) and can reduce the cost of using electrical devices by Rp. 16,881 (12.01%).

Effective Analytic and Remotely Monitoring Smart Drug Delivery System based on IoMT with KNN classifier of Epilepsy Patients

Chronic, non-communicable brain disorder, epilepsy is one of the most severe neurologic disorders. Worldwide, about 50 million individuals (2.5 percent) have Epilepsy, rendering it one of the world's most severe neurological disorders. [1]. About 80% of individuals with epilepsy work in countries with small to modest income. A medically refractory solution for the seizure control for a large fraction of affected patients. Here we explain the IMoT structure for a single drug delivery network. This has resulted in injection of drugs when seizure seizures have been identified. A powerful micro-pump electromagnetically powered with a polydimethylsiloxane (PDMS) diaphragm was used to distribute the drug. Simulink ® and ThingspeakTM were the prototype for the solution. The findings of the simulation reveal that the device proposed preserves high precision performance while substantially reducing power usage (8-26 %)..

Monitoring the Consumption of Electrical Energy Based on the Internet of Things Applications

<p class="0abstract">One of the instrumental functional overheads in many commercial edifices and industrial plants is the electricity bill. The design and development of a Smart Power monitoring device used to make monitoring on the electrical parameters represented as voltage, current, and power of Wasit university buildings. The system has a unit with smart sensing to detect and control the electrical devices employed for daily activities by following different tariff rates. It has the capability to decrease consumer costs improving grid stability. A developed model was broadly examined and experimental results comparing these results with devices of conventional measuring. The Arduino based wireless powering meter is a non-invasive existing meter for domiciliary power with a WI-FI Connection. A split-core is used to measure the current transformers. 802.11b connection is a means for transmitting data through the home’s wireless router to the base station and monitoring web portal based on wireless sensor network. A clear projection for domestic data use is one of the aims of this project. By these data, it can supply estimation to consuming power. Optimizing and reducing power usage are the objectives of providing such data.</p>

All-in-one Power Conversion System for a Smart Factory

This paper investigates the incorporation of a PV-ESS linked, all-in-one power conversion system (PCS) at a small factory, in an attempt to improve the factory’s resilience against the increase in load due to facility expansion. The aforementioned factory was installed with 210kWh PV and 550kWh ESS, both of which were simultaneously managed by 250kW hybrid power conversion system. This independent operation of the factory through the PCS was proven to be efficient and economical, because of the reduced power usage and the sale of surplus electricity.

Energy-efficient retrofitting strategies for healthcare facilities in hot-humid climate: Parametric and economical analysis

All living beings depend on energy for survival, and modern civilizations will continue to thrive only if existing sources of energy can be developed to meet the growing demand. With the universal urge to reduce power usage in the building environment, there are broad discrepancies between energy efficiency intention and the realistic operation of buildings. Implementing current mitigation strategies tends to be gradual and requires a ‘whole-system’ approach to the issue.In Egyptian buildings, energy demand increased dramatically with the increasing necessity to acquire indoor thermal comfort conditions. Simultaneous growth in residential and commercial developments necessitate increasing power production to face new demands. Energy needs in facilities are growing annually due to the expansion in HVAC (Heating, Ventilation & Air Conditioning) systems operating hours. Minimizing power demand and encouraging the use of green energy sources, protecting the planet from global warming impacts, and depleting the ozone layer is beneficial.High temperatures and high humidity levels in hot and humid climate zones such as Alexandria in Egypt cause human discomfort, resulting in high HVAC energy consumption. Apart from medical equipment, power, and infection controls, hospitals utilize substantial amounts of HVAC energy. To clarify Egyptian hospitals ' energy consumption, the on-going case study is conducted on a hospital accessible to the researcher at Alexandria, Egypt. The purpose of this study is to explore medical facilities' energy requirements and to assess the possible energy savings of present buildings in Egypt. Using the DesignBuilder simulator platform, a prototype was built for medical institution underdevelopment. Depending on the hospital’s construction, mechanical consultants’ documentation, and EUI, the model is validated. Firstly, the initial model is adjusted to the latest outdoor design conditions and weather database information endorsed by ASHRAE (American Heating, Refrigeration, and Air Conditioning Engineers Society) and NREL (National Renewable Energy Laboratory). Analysis of energy-efficient methods influencing yearly HVAC power utilization and total building power is examined. The analysis gives information about the increase in energy efficiency in medical institutions achieving thermal comfort in Alexandria that would allow designers to sufficiently limit buildings ' energy consumption.For the autonomous temperature and moisture control and influence on the HVAC system, a DOAS (Dedicated Outdoor Air Systems) was introduced asserting substantial energy-savings for both HVAC and the entire building electricity utilization.The study reveals that about 67% energy savings and operating costs can be achieved through efficient retrofitting and systems right sizing.Through economic analysis, this study provides new energy opportunities for new medical facilities in hot-humid climatic regions.

Artificial Neural Network Based Power Management for Smart Street Lighting Systems

The modern ways to empower the ecofriendly people also insists the necessity to cutting back of energy consumption. The minimizing the energy consumption would in turn reduce the rate of carbon emission, resulting in a cleaner air quality and higher standard of living by paving way for a cleaner planet. The increasing demand on power requirement is also one of the important reason for minimizing the energy consumption. The paper tries to decrease the energy usage of the street light system as the lighting systems in the street does not have an efficient way of managing and controlling the power flow in them as they are incapable of taking into consideration the prevailing demands on the intensity of light. So the paper puts forwards the idea of power management in the smart street lighting to control efficiently the power consumption by comparing the intensity of the light with the weather conditions. The artificial neural networks is used in power management of the street lighting in the proposed method. The evaluation of the method show up with the results that produce the better management of the power and the reduced power usage in street lights.

Energy-Efficient IoT Sensor Calibration With Deep Reinforcement Learning

The modern development of ultra-durable and energy-efficient IoT based communication sensors has much application in modern telecommunication and networking sectors. Sensor calibration to reduce power usage is beneficial to minimizing energy consumption in sensors as well as improve the efficiency of devices. Reinforcement learning (RL) has been received much attention from researchers and now widely applied in many study fields to achieve intelligent automation. Though various types of sensors have been widely used in the field of IoT, rare researches were conducted in resource optimizing. In this novel research, a new style of power conservation has been explored with the help of RL to make a new generation of IoT devices with calibrated power sources to maximize resource utilization. A closed grid multiple power source based control for sensor resource utilization has been introduced. Our proposed model using Deep Q learning (DQN) enables IoT sensors to maximize its resource utilization. This research focuses solely on the energy-efficient sensor calibration and simulation results show promising performance of the proposed method.

Performance Analysis Of Grid Tie Inverter With Power Limiter To Increase Utility Power Reduction In One Way kWh Meter Circuit

The use of grid tie inverter (GTI) in household electricity is intended to reduce the use of electricity from utilities. The configuration of GTI usually does not use batteries and the excess power from PV will be sent to the grid so that it will substitute utility electricity with electricity from GTI. However, this can occur when follow net metering program by installing a export-import kwh meters (two-way kwh meter) or follow feed in tariff program. If the kwh meter used does not support this capability or not following both program, the electric power of GTI will not substitute power from the utility. GTI with power limiter allows the inverter to work like a GTI in general but does not send excess power to the utility. The excess power from PV can be stored into the battery so that when the power shortage of PV will be substituted with power stored in the battery is not from the utility. In this research, conducted a study of the performance of the GTI with a power limiter and compared it with the GTI without a power limiter that works on an electricity network. The results of the study show that the use of GTI with a power limiter can increase the reduction in power usage from utilities by up to 40%.