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(Volume: 3, Issue: 1)
IoT and Solar-Powered Mobile Battery Health Monitoring System
Almost all the tasks in this smart technological era relies on the manipulation of mobile devices. However, not at all times, the mobile devices could impart uninterrupted service because of their limited battery life. It is at this instant the Lithium-ion batteries (LiBs), which were known for their high- power density, extended life cycle and reduced self- discharge rates came into existence, increasing the usage times of mobile devices. These batteries are encompassed with a Battery Management Unit (BMU), alternatively called as Battery Management System (BMS), during the time of manufacture to achieve two chief tasks: (i) To make measurements on current, voltage or temperature for cell balancing and (ii) Regulating cell charging or discharging rates. However, the real-time monitoring of battery’s health to maximize the device usage with optimal power consumption is a big question here. Further, electrical energy was only the choice for charging the mobile devices. But this situation has changed with the advent of Internet of Things (IoT), cloud computing resources and renewable energy sources. With IoT and cloud computing, the machine-to-machine or device-device communication is possible in real-time on a ‘pay as you use’ manner. Further, opting for renewable energy resources can massively cut down or supplement the electricity usage from non-renewable resources. Recently, three researchers, Brajendra Prajapati, Bhawani Singh Rathore and Dr. Divakar Singh from Barkatullah University, Madhya Pradesh, India too have aimed at achieving an intelligent battery health monitoring system using IoT in mobile devices. Further, they have specially designed a mobile back cover that contains solar cells to harness solar power for supplementarily charging the mobile devices, which could be a boon at remote areas with no electricity for charging!!! “The proposed mobile battery health monitoring system aims to provide users with a reliable and sustainable power supply, ensuring non-discharge and extended battery life”, the authors say. The authors also compliment the IoT technology, as it enabled the BMS and the solar power storage as well as intake modules in mobile back cover to go hand in hand for sustaining the battery charging limits with zero discharging rates in mobile devices. Since the mobile devices have extensive utilization as consumer electronics, wearable healthcare and non- healthcare devices, industrial or robotic machines and smart-home devices, the research on intelligent and real-time monitoring of battery health and its charging/discharging times to achieve uninterrupted service, enhanced performance and reduced energy consumption has a great scope in the future. Image courtesy: www.vecteezy.com
Simplex-Lattice Design For Tastier And Nutritious Multigrain Waffle Ice Cream Cone Production
No one says “NO” to enjoy delicious ice creams, being served in crunchy Waffle ice cream cones. However, these wafer cones are usually made with Refined Wheat Flour (RWF) that lacks fibre and nutrient contents with high glycaemic index, harming bodily health. Nowadays, childhood overweight and obesity has become more common. World Health Organization (WHO) alerts that the energy-dense foods, which naturally have more fat and sugars, and less amounts of vitamins, minerals and other healthy micronutrients are the key factors for this worst scenario. Hence, various alternatives to replace RWF have been opted in the food industry to safeguard the health of children, who are the major victims of consuming these high-carb ice cream cones. Manufacturing waffle ice cream cones from healthier, gluten-free choices like, corn or millets have become a trend now. However, meeting a good taste and aroma, along with improved crunchiness, in such healthier waffle cones is quite difficult. In fact, the blending of flours from healthier cereals in right proportions to get a tastier, aromatic, crunchier, colorful and preservable waffle cone than its conventional RWF counterparts has actually grown to be a very hot research theme, involving statistical modelling and analysis, optimization procedures or even the machine learning approaches. A team of seven Indian researchers, including Sachin K Sonawane from the School of Biotechnology and Bioinformatics, D. Y. Patil Deemed to be University, Mumbai, have attempted to formulate a multigrain waffle cone using optimal blending proportions of Finger millet (ragi), Buckwheat, Amaranth, and Pearl millet (Bajra) flours. In their article in Food Chemistry Advances, Elsevier, vol. 4, the researchers have used simplex lattice designs, Response Surface Methodology (RSM), regression analysis and Analysis of Variance (ANOVA) for this purpose, setting parameters like, crispiness, aroma, appearance, ice cream holding time, color, aroma, hardness and taste as the desired responses. The authors have also studied the microbial activity during storage for knowing the time to which the multigrain cone can be kept fresh enough for serving the ice creams. Since nutritious and balanced food would be of high demand in future, the upcoming researchers can impart better optimization or machine learning approaches to improve the food quality, in terms of appearance, taste and nutrition.
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Research Insisted On Improving Network Security In SDNs
Since 2011, Software Defined Networks (SDNs) have attracted most academic, organizational and industrial networking applications. There are various reasons to support this notion and they are: (i) The centralized and programmable controlling of networks using a SDN controller; (ii) The decoupling of the control plane from the data plane, which means the entity for traffic decision and traffic flow are detached ; (iii) Eliminates manual and device-specific programmability, control and configurability of network devices in traditional networks, easing up network management using software applications; (iv) Improved network virtualization and interoperability through OpenFlow protocol and (v) Improved network security because of the decoupling of control plane and attack-prone data plane. However, the SDN networks too cannot seclude from security attacks. This is because the centralized SDN controller or the OpenFlow communication between the controller and the communicating devices or the network interfaces, on getting controlled by an intruder, will just result in Denial of Service (DoS), eavesdropping attacks and serious data security threats. Sukhvinder Singh and S. K. V. Jayakumar, the former from Dr. B. R. Ambedkar Institute of Technology, Port Blair, and the latter from Pondicherry Central University, Kalapet have investigated various attacks found in SDNs, rendering a detailed review on the associated detection methodologies in Wireless Personal Communications, Springer, vol. 114. As per the researchers, the SDNs are most-prone to DoS attacks. The researchers justify this point, as the attacker can create excessive network traffic using fake data from compromised network nodes, making it difficult for the centralized controller to maintain a smoothly- controlled network traffic flow. Additionally, the researchers have examined various attack detection mechanisms, involving various soft computing and machine learning techniques, which might aid in improving the network performance and the Quality of Service (QoS). Thus, the researchers have provided great directions for improving security in SDNs in future. Since the SDNs have wide applicability in cloud computing, Internet of Things (IoTs), Wide Area Networks (WANs) and 5G networks, it is in the hands of the impending researchers to preserve network security with proper attack detection and control mechanisms. Image courtesy: www.vecteezy.com
FPGA-Based Parallel Decoder Architecture For 5G Wireless Communication
Decoder architectures have a crucial role in ensuring reliable and efficient data transmission, especially when it comes to 5G Wireless communications. Be it demodulation, channel decoding, error correction coding, deinterleaving, source decoding, frame synchronization or signal quality assessment, the decoder architectures in 5G wireless communication systems are aimed at providing low latency and high throughput communication across varying channel conditions, noise and interference. Polar codes are a type of error-correcting codes used in 5G decoders, which uses channel polarization for accomplishing reliable communication over a binary input discrete memoryless channel. They are used for sending uplink/ downlink control information in 5G networks with high mobility and low encoding or decoding complexity by employing the Successive Cancellation (SC) decoding algorithm. Recently, numerous researchers have examined various hardware decoder architectures to handle SC decoding of polar codes. However, there is always a room for improvement, when it comes to handling longer code lengths with high throughput, low latency and optimal hardware utilization. Dinesh Kumar Devadoss and Shantha Selvakumari Ramapackiam from Mepco Schlenk Engineering College, Sivakasi, India have put forth a fully parallel, Low-Density Parity-Check Code (LDPC)-based polar decoder architecture for 5G wireless communications. In their article in ETRI journal, Wiley, the researchers have employed the Virtex-7 Field Programmable Gate Array (FPGA) to design a decoder that can handle binary input of short-to-intermediate code lengths. Additionally, the authors have implemented the decoder using the Xilinx ultra-scale FPGA to confirm its supremacy on error correcting performance and hardware efficiency in 5G wireless communications. Since the authors state that their LDPC-like BP decoder for polar code is the first FPGA-implemented decoder, the presented system actually serves as a guide for the new researchers to propose improved decoding architectures.
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Optimized PI Controllers For Grid-Tied PV-Based Electric Vehicles
The awareness on the alarming increase of green house gas emissions and the need to switch over to non-gasoline fuels due to the hiking costs has led to the development of Electric Vehicles (EVs). Though EVs ignore internal combustion engines, which operate on petrol or diesel, and run using the comparatively less-expensive electricity-powered motors, the electricity being generated from non-renewable resources like fossil fuels requires special attention. Hence, EVs operated on renewable energy resources like, solar or wind power becomes utmost vital to cut down excessive costs and to conserve non-renewable energy for future. In recent days, designing highly efficient solar-powered EVs have turned out to be a massive research area because of the widespread availability of solar energy than the other renewable energy resources. However, the solar power changes with changing weather or climatic conditions. Hence, it is not enough or fully made available to drive the high-power electric motor in EVs. As a consequence, high gain dc–dc converters like, Boost, Buck-Boost, Zeta, SEPIC and Cuk, along with appropriate controller such as Proportional Integral (PI), have been adopted in PV (Photovoltaic)- powered EVs to maximize the available energy and to meet the operating demands. However, the proper tuning of PI controllers is not always possible due to the intermittency in PV systems. J. Aran Glenn and Srinivasan Alavandar from AMET Deemed to be University and Agni College of Technology, respectively, from Chennai, Tamil Nadu have attempted to alleviate the afore-mentioned issues in the Grid- Tied PV- Based Electric Vehicles using a hybrid optimized PI controller design. In their article in Intelligent Automation & Soft Computing, vol. 36, no. 2, the researchers have initially enhanced the unregulated DC output voltage from PV using the Trans Z-source Based Luo converter (TZSBLC). Further, they have used the Lion Grey Wolf Optimization algorithm for optimally-designing the PI controller to enhance the performance of the integrated converter, in terms of settling time, peak overshoot and Total Harmonic Distortion (THD). Additionally, the authors have used three phase and single-phase Voltage Source Inverters (VSI) to convert the PV-based and the grid-based DC output, respectively, into AC output for driving the Brushless Direct Current Motor (BLDC) motor in EV. Here too, the PI controller has been used for taking control on the speed of the BLDC motor. Since emission-free transportation and decarbonized energy production is only aimed in future, the researchers have a great scope to contribute in this domain. Image courtesy: www.freepik.com
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