Cognitive Computing and Cyber Physical Systems

Off-grid hybrid distribution systems are innovative and environmentally friendly ways to address the energy needs of remote or isolated communities or facilities by combining a number of power generation and energy storage sources. These systems are made to function independently from the primary electrical grid, which makes them perfect for areas with little or no access to centralized electrical infrastructure. In this work, designed an effective microgrid system with integration of distributed power sources such as wind turbine and Photovoltaic system (PV). Moreover, adaptive neuro fuzzy inference system (ANFIS) is developed in this study to track the maximum power from PV panels under various uncertain conditions. Further, due to intermittent nature of the wind speed and irradiance levels, battery system is designed in this work for stable and reliable operation of microgrid system. Moreover, the battery performance and ANFIS-based maximum power point tracking (MPPT) are investigated. As per simulation findings, ANFIS based MPPT approach provides an effective outcome in terms of settling time, efficiency and accuracy in suggested microgrid systems.

During the design of Application-Specific Integrated Circuits, a whole adder logic circuit plays a significant role. The full adder is a fundamental part of the majority of VLSI and DSP applications. Power consumption in full adders is one of the key factors; hence it is necessary to build full adders with low power consumption. Full adders are developed in this work employing full swing AND, OR, and XOR gates and compared with pass transistor logic (PTL) based AND, OR, and XOR gates, and complementary metal oxide semiconductor logic (CMOS) based AND gate, OR gate, and XOR gate. The Mentor Graphics Tool is used to construct and simulate every planned circuit. After receiving simulation data, we compared the power consumption, delay and PDP of several complete adder-based logic designs. In the proposed full swing XOR, the power dissipation and delay is decreased by 10.5% and 9.8% respectively and hence the full swing full adder PDP is decreased by 0.6%. As compared to alternative full adder designs based on logic, full swing by using gates like AND gate, by using the OR gate, and with the help XOR gate, full adder design consumes less power and hence suitable for low power applications.

In the modern era of renewable energy generation and distribution, injecting solar power into the utility grid has gained universal recognition, also solar energy plays a crucial role for smart cities development. Grid-connected asymmetrical multilevel inverters have undergone significant development for integrating solar into the utility grid. This article aims to implement a 15-level asymmetrical inverter in a single-phase grid-integrated PV system and analyses the proposed system working with a 15-level inverter. This inverter topology has fewer switching devices, design with three DC sources and can generate fifteen output voltage levels; in this proposed system, these three DC sources are designed by three PV modules and three conventional boost converters. P&O (Perturb and Observe) Algorithm was implemented on each boost converter to extract the maximum power from three PV modules. The proposed system is simulated in MATLAB 2023a with toolboxes. The simulation results show whether the inverter can export the power to the grid under various solar irradiance conditions. The solar-based proposed system is well suited for groups of houses in smart cities.

The potential of electric automobiles to discharge their batteries to the power grid (namely V2G technology) is discussed in this article as a way to lessen pollution and provide extra services, including income generation and grid reliance. The widespread use of electric cars might provide difficulties for the electrical infrastructure, such as power outages, overloading of transformers, and variations in bus voltage. The electrical grid and electric cars are connected through a middleman called an aggregator. This article investigates novel technologies and coordination mechanisms to control the discharging and charging of electric cars. In addition to that, Various optimization techniques are reviewed and also try to explain about challenges and future advances in the EV charging process and discharging process.

The relevance of ultra-low-voltage (ULV) operation for attaining minimal energy usage has increased recently. The fundamental building element of computational arithmetic in many computer and signal/image processing applications is the full adder. An innovative 1-bit hybrid adder circuit that uses both multi-threshold voltage (MVT) transistor logic and GDI (gate-diffusion input) logic is disclosed. The suggested motivation of the Multi Threshold Voltage-gate-diffusion input hybrid adder design is to furnish low energy efficient utilization with a small footprint. Standard 45 nano-meter CMOS process technology is used to simulate the suggested hybrid architecture with a ULV of 0.2 V. The suggested design made considerable improvements in contrast to the previous published designs, yielding >57% and 92% reductions Using only 14 transistors in the Energy and Delay Product respectively, according to the post-layout simulation findings. The suggested design technique produces full functionality, which shows resistance against the processes of global, local variations. The suggested design offers >57% energy efficient compared to the current efforts, according to energy measures that are adjusted for 32 and 22 nm technologies.

These days, we find many batteries used in Electric Vehicles are burning or blasting due to overcharging or long time charging. During such condition, the battery body temperature may rise, to avoid these types of mishaps, here this special type of battery charger is designed using the latest technology such that the battery can be charged using wireless technology and at the same time the battery voltage and its body temperature data will be monitored continuously through an embedded system. An important feature added to the system is that if the battery body temperature raises more than the threshold value, immediately supply to the battery will be disconnected automatically and an alarm will be energized. Once the alarm is energized it remains in energized condition until the reset button is activated. The battery condition will be monitored digitally and it will be displayed through an LCD interfaced with Arduino board. Another important feature added to the system is that entire information will be transmitted to the concerned mobile phone through a WiFi module using IOT technology. Wireless charging is a new technology for charging batteries that allows charging over short distances without cables. The advantage of wireless charging is that charging is quicker and easier, we need not have to plug and unplug each time, simply by placing the vehicle in its parking place where the power transmitting coil is installed under the ground, the battery starts charging automatically.

In present scenario renewable energy sources are crucial and they taking lead to supply power to the consumers. These renewable energy sources mostly generate dc power, which are to be converted into alternating supply for consumer’s use. So there is an impelling need of inverter to convert direct current supply into alternating supply. These inverters are classified into numerous types and depending upon application, the type of inverter is used. In general, a normal inverter will produce square wave output where as a multi-level Inverter will produce staircase waveform which is nearer to sinusoidal. By the level upgrading, the output waveform is very near to the pure sine nature. In this paper, a comparative analysis between the basic Sine PWM and advanced Third Harmonic Injection method for a three level Neutral Point Clamped Inverter (NPC).

Improper disposal of single use plastic bottles leads to many problems including danger to marine life and land pollution. Burning of plastic in turn releases dioxins and polychloride biphenyls. They are very harmful if inhaled and are threat to vegetation too. Manual sorting of plastic bottles and safe disposal is not an easy task. A lot of recycling initiatives use manual sorting for plastic recycling, which depends on plant staff visually identifying and selecting plastic bottles as they move along the conveyor belt. Automatic sorting of plastic bottles has advantage of non-intrusive sorting, speed, consistency, cost effectiveness in long run and even prevents health hazards to workers working in recycling environment. As a result, it is imperative to replace human sorting systems with intelligent automated systems. In this study, convolutional neural network architectures such as YOLOv5 and YOLOv8 were utilized to detect plastic bottles in images. Despite YOLOv8 having more parameters and requiring more computation time, it was found that YOLOv8 outperformed YOLOv5 in accurately identifying plastic bottles in the images.

The escalating frequency of fatal crashes has led to an enhanced focus on road safety, resulting in the creation of diverse driver assistance systems. Several instances of these systems encompass active braking, lane departure warning, cruise control, lane maintaining, and numerous additional examples. However, the primary objective of this research is to examine the effectiveness and reliability of a model predictive control (MPC) and a proportional integral derivative (PID) control in executing lane keeping maneuvers within an autonomous vehicle. In this paper, a custom controller for autonomous lane-changing maneuvers is developed by utilizing the Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) controllers. Different trajectory models are employed to assess the overall effectiveness of the designed model, showcasing its superiority over existing models.

MANET (Ad-Hoc Mobile Network) is a systematic aggregation of identical types and varieties of nodes. These nodes are dynamically created as desirable and capable of communicating, barring a primary infrastructure-based system. As these nodes connect devices such as mobiles, tablets, etc., they can develop a range of provider delivery with an appreciation for network performance. Network traffic is an essential assignment in the ad-hoc mobile area network. Route agreements efficiently enhance carrier exceptionality in better access, partial delivery of packets, and minimal storage delays. The predominant motive of this analysis is to evaluate the legal method concerning the parameters of the various quality of service enhancement services. The simulation outcomes affirm that the proposed scenario affords a better dimension of the exceptional testing of the compliance offerings at MANET.

The increasing demand for fuel due to the growth of automobiles in the market has led to the need for on-demand fuel supply applications that depend on user orders and requirements. When a vehicle runs out of fuel, it can be a hassle for the owner to push the car or seek help to reach the nearest gas station. For older people and those who are medically ill, this task can be even more difficult. Additionally, people must go to gas stations to fill up generators. To address these issues, we introduce a new solution for vehicle refueling and emergency power supplies through the development of an on-demand fuel delivery application. This application provides door-to-door coverage and allows end users to choose the type of fuel they need, order it, and receive it with ease. The outcome of this research paper will be the development of a mobile application using Flutter framework that offers a range of functionalities catering to both customers and fuel station owners. The application aims to provide a convenient platform for customers to order fuel, locate nearby gas stations, and assist owners in efficiently managing orders and monitoring station availability. By utilizing Flutter, a cross-platform development framework, the application will be compatible with both Android and iOS devices, ensuring a broader reach and accessibility for users. Flutter's rich UI capabilities and native-like performance will enable the creation of a visually appealing and seamless user experience.

In 21st century, there is huge political unrests among political leaders in many developing countries, in spite of Boom of Internet users, still the elections are held in semi-old fashion. The cost associated with these elections (i.e. appliances, workforce related, transport etc.) act as burden on tax payer's money & cuts the huge possibilities of R&D in any nation. Specially in south-east nations, Indians (NRIs) move abroad for various reasons; To demonstrate the feasibility of our protocol in real-world scenarios, we have implemented it using Ethereum's blockchain as a public bulletin board. As a result, casting vote for them becomes very difficult, hence we created mechanism where NRIs can vote securely using their passports.

Efficient and personalized human-robot interaction is a critical goal in robotics research. In this study, we propose a novel approach to enhance human-robot interaction by integrating facial sentiment analysis, object detection, and behavior prediction into a bot powered by Blender face technology. Our proposed system enables the bot to perceive and respond to the emotional states and preferences of individuals, creating a more intuitive and engaging interaction experience. By integrating lip syncing capabilities and object recognition functionality through webcam integration, the proposed solution seeks to enhance the authenticity and intuitiveness of user experiences. Through the utilization of Blender animation tools and Natural Language Processing methods, our solution facilitates seamless interaction between humans and neuro robots, contributing to improved outcomes and well-being.

For the next generation of wireless communication networks to advance, massive multi-user multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM) systems are essential. Nevertheless, due to the concurrent presence of several users and the frequency-selective fading channel, identifying sent data in such systems proves to be a daunting issue. This study proposes a huge MU-MIMO-OFDM system-compatible coordinate descent-based equalization-based soft output data identification technique. This algorithm's major goals are to improve the estimation of transmitted data symbols and effectively deal with inter-user interference. By exploiting the sparse nature of the channel impulse response, the data detection problem as a joint sparse signal recovery and symbol detection task. Then, the coordinate descent algorithm, which iteratively updates the estimated symbols and exploits the sparsity structure of the channel has been implemented. These soft outputs can be utilized in subsequent stages of the communication system, such as channel decoding or interference cancellation. The simulation results clearly illustrate the superiority of the proposed method over existing detection techniques in terms of bit error rate (BER) performance. The algorithm showcases remarkable enhancements in detection accuracy, even in challenging scenarios involving a substantial number of users and severe channel conditions. When the number of base stations is increased from 32 to 128, the proposed algorithm demonstrates a substantial 76% reduction in bit error rate (BER). In contrast, conventional methods only achieve a value of approximately 60% reduction in BER under the same conditions.

In this paper, spatially multiplexed hybrid binary phase shift keying-multi-pulse pulse position modulation (BPSK-MPPM) based 8-core multicore fiber (MCF) interconnect system is suggested for the foreseeable future exa-scale optical interconnect (OI) applications. The impact of different characteristic parameters like optical signal to noise ratio (OSNR), launch power, and inter-core crosstalk (XT) on bit error rate (BER) of hybrid BPSK-MPPM modulated OI system are discussed in detail. Further, error probability performance of conventional BPSK and hybrid modulation format are compared for 40 Gbps per channel. It is shown that the proposed hybrid scheme is suitable for futuristic data center, high-end computing system and silicon photonic transceiver chips.

Optical links play a crucial role in modern communication systems, enabling high-speed data transmission over long distances with minimal loss and interference. As the demand for faster and more reliable networks continues to grow, evaluating the performance of optical links becomes paramount. There are several approaches to developing performance prediction strategies for optical links, including analytical models, numerical simulations, and experimental measurements. Analytical models are based on mathematical equations and can provide quick and accurate predictions of the link performance for simple systems. Numerical simulations use computer software to solve complex equations and simulate the link performance for more realistic systems. The prominent strategies include: link budget analysis; chromatic dispersion compensation; nonlinear impairment mitigation; error correcting codes. This work mainly focusses on analyzing the performance of optical link with various prediction strategies (hard decision-FEC, soft decision-FEC and probabilistic shaping)) using forward error correcting codes (FEC). The symbol error rate, bit error rate and achievable information rates have been analyzed for aforementioned strategies with and without FEC.

Surface acoustic wave sensors are becoming more and more essential in research. The research has advanced in such a way that SAW sensors are now used in many different fields. The application areas of SAW sensor include gas sensing, biosensor, measurement of many physical parameters like humidity, pressure, temperature and torque. In this study, the SAW sensor is presented as a nitrogen gas sensor. Nanomaterials are introduced to a conventional SAW sensor to strengthen the sensor's performance. The most frequently used nano - materials for applications in gas detection is ZnO. Comsol Multiphysics is used to design a 2D SAW-based gas sensor using ZnO as the sensing material. Finite element analysis (FEA) is used in sensor characterization. Testing is done to determine whether nitrogen gas is present or not in the sensor. The sensor's sensitivity varies depending on whether there is gas present or not while operating at the same frequency. The sensor's frequency range is 3 MHz. Nitrogen gas is present in concentrations varying from 10 ppm to hundreds of ppm. With a rise in concentration, the sensor showed excellent linearity.

A unit cell design of a thin film solar cell incorporating turnstile diamond dipole nanoantenna as a means of light trapping structure is proposed and investigated. Diamond dipole nanoantenna (DDNA) is a transformed version of the conventional dipole nanoantenna whereby the arms of the dipole nanoantenna are replaced by diamond shaped nanoparticles. In contrast to the dipole nanoantenna, DDNA offers larger area for field confinement and it resonates in the maximum solar spectrum range. The reduction of reflection losses along with generation of localized surface plasmons leads to improved photovoltaic characteristics of the thin film solar cell. The suggested TFSC model offers 99% absorption with 1.52 times photocurrent calculated based on finite element approach.

This paper presents a novel approach utilizing an artificial neural network (ANN) for optical wireless communication (OWC) between satellites in geosynchronous earth orbit and lower earth orbit, covering a distance of 45000 km. The objective of this ANN based intersatellite optical wireless communication (IsOWC) system is to intelligently predict the quality factor considering different wavelengths. To enhance the transmission performance between these satellite systems, the mean squared error (MSE) is minimized using the Levenberg–Marquardt optimizer. Remarkably, after 25 epochs, the MSE value reaches an impressive 0.000373. The results demonstrate that the ANN-based learning outperforms other machine learning algorithms, exhibiting a significantly lower MSE. Furthermore, this system has a high convergence rate as well as resistant to outliers and overfitting. Even if the number of features is small, it can be predicted accurately. Such systems hold great promise for future wireless designs and integrations, spanning from satellite to terrestrial and underwater OWC systems.

This work presents an ultra-wideband tunable graphene-based metasurface absorber for the terahertz (THz) gap region of the electromagnetic (EM) spectrum. The proposed absorber provides an absorption bandwidth (BW) of 7.8 THz (fractional BW = 195%) with absorptivity A(f) $$\ge $$ ≥ 90%, i.e., from 0.1 to 7.9 THz. The impedance matching between free space and the absorber’s surface has been achieved by engraving different shapes of slots on the top graphene layer. The working principle behind the UWB absorption mechanism has also been studied with the help of parametric studies and field plots. The thickness of the metasurface is only 2 $$\upmu $$ μ m, i.e., $$\lambda _g$$ λ g /958.3, where $$\lambda _g$$ λ g has been computed at 0.1 THz, thus, maintaining the ultra-thin nature required for the metasurface design in the THz regime. The absorber’s periodicity is also quite less, i.e., 6 $$\upmu $$ μ m ( $$\lambda _g$$ λ g /319.43), which is sufficient to achieve an effective homogeneity condition. The four-fold symmetry in the design makes the structure polarization insensitive to the incoming plane wave. The metasurface also works well for a wide incidence angle ( $$\theta $$ θ ) under both transverse electric (TE) and transverse magnetic (TM) polarizations. The A(f) $$\ge $$ ≥ 80% has been achieved for $$\theta $$ θ up to 45 $$^\circ $$ ∘ . In addition, the absorber provides full-width at half-maxima (FWHM) BW in the complete frequency range, i.e., from 0.1 to 7.9 THz. Hence, the proposed metasurface absorber is found suitable for suppressing/absorbing unwanted electromagnetic radiation in a close indoor environment for smart city-enabled Internet of Things (IoT) applications.

This research paper presents a study on wireless energy harvesting (WEH) protocols and their impact on the performance of sensor networks. A time switching (TS)-based WEH protocol is proposed, which allows sensor nodes to switch between energy harvesting and data transmission modes. The primary objective of this research is to maximize the uplink (UL) sum throughput while considering the constraint of a minimum downlink (DL) throughput. To achieve this, an optimization problem is formulated, and the Karush-Kuhn-Tucker (KKT) conditions and Lagrangian multiplier are employed to solve the optimization problem. Additionally, a UL-DL channel gain-based unequal sensor node operating time scheme is introduced. The results of the study demonstrate that increasing the DL threshold data rate enhances UL performance in terms of sum throughput and outage. Moreover, the proposed channel gain-based unequal operating time scheme outperforms the equal sensor node operating time approach.

This paper provides an idea to design a wideband antenna suitable for UHF-band aircraft application. The blade antenna (BA) has been simulated for different elementary parameters using CST simulator. Antenna performance characteristic with the parametric variation of the antenna model have been studied and demonstrated. The simulation results of the designed antenna show 3.18 dBi gain, and 53-degree half power beamwidth (HPBW) over the entire frequency range 0.9 GHz to 2.0 GHz. Further, the designed antenna a very good return loss performance with VSWR <2.2 in the entire frequency band. This antenna can find its application in aircraft GPS navigation system and datalink operation as well.

There are several factors which introduces transmission losses in deep water such as: surface reflections; surface ducts; bottom bounce; convergence zones; deep sound channel; reliable acoustic path; and ambient noise. Hence, it is crucial to model the acoustic channel characteristics and evaluate the effect of transmission losses by considering aforementioned factors inorder to employ the network for specific application. This study primarily aims to estimate the transmission losses caused by surface reflections in deep water environments using a multipath acoustic channel model. The simulation is conducted, considering the impact of absorption, sound speed, temperature, and salinity. The depth of the network scenario is varied to analyze the effects of these factors on the transmission losses. It is evident from simulation results, the acoustic velocity increased by 250 m/s when the depth varies from 100 m to 7000 m and temperature decreased from 30 ℃ to 4 ℃. Similarly, when the salinity increased from 30 ppt to 35 ppt, the acoustic velocity has been increased by 7.14% in deep water. An increase in transmission loss of 5 dB has been attained when the wind speed (W) increased from 4 m/s to 12.5 m/s. Similarly, the transmission losses are increased by 8 dB when the angle of incidence (Theta) increased from 20° to 30°.

Wireless Ad hoc networks are networks connecting mobile devices that are self-contained. It’s these networks simplicity and ease of implementation make them the best choice for frontline communications, incident management, and other related applications when dependable infrastructure is not easily accessible. The applicability of such networks has been challenging due to partial bandwidth, energy restrictions, and unexpected system topologies. Recent years have seen resurgence in this area’s research. Specifically in routing, security and multicast concerns. The paper focuses on multicast routing in peer-to-peer networks in this paper. In this work, the source packet dumping, a fresh multicast routing system has been presented. Based on restrictions on hop distance, the connectivity routes between providers and group members are established as a single hop/multihop. In order to ensure effective data dissemination, a probabilistic data forwarding mechanism has been suggested. The simulation results demonstrated the performance of suggested routing protocol comparison to factors that define an ad hoc network. It is evident from simulation results, that the suggested protocol delivers effective data distribution and is resistant to topology changes.

In the shallow water environment, the water surface, and the seafloor act as reflective boundaries for the sound waves. When a sound wave encounters these boundaries, it undergoes reflection, bouncing back and forth between the surface and the bottom. As a result, the sound energy is distributed among various paths, leading to multipath arrivals at the receiver. The repeated reflections contribute to the complexity of the sound propagation in shallow water. This multipath propagation can cause interference and fading, making the received signals challenging to decode, interpret accurately, and transmission losses. Therefore, proper modelling of channel is essential inoreder to deploy a network with high accuracy. In this work, we have developed and analyzed an acoustic multipath channel model to investigate the impact of mixed layer depth and near field anomaly on transmission losses in underwater environments. The main focus is on understanding how various underwater medium parameters, such as temperature, salinity, depth, and pH, affect the transmission losses. It is evident from simulation results; acoustic velocity has increased by 30 m/s when the temperature reduced from 30 ℃ to 14 ℃ and 7 m/s when the salinity increased from 30 ppt to 35 ppt. Transmission losses are increased by 58.8% when the mixed layer depth (MLD) increased from 10 m to 95 m. Whereas, these losses are reduced by 43.7% when the near field anomaly (KL) increased from 7 dB to 20 dB.

One of the main substances that significantly affects ecosystems is water. Unfortunately, with increased urbanization, sewage, abstraction of chemical fertilizers and pesticides in agriculture, which contaminate water, is now widely exploited. To monitor quality of the water across wide region, like rivers, lakes, or hydroponics, it is thus required to install a system. According to the state of world today, IoT and distant sensing methods are utilized in a variety of study fields to monitor, collect and analyze data from distant locations. The proposed system-DCWQM includes a wide variety of sensors interfaced to ESP-32 for measuring physical and chemical parameters of drinking water. This method allows analyzing of data that has been posted online through Blynk App and the real-time assessment of water body quality.

The Smart IV bag monitoring system is designed to address the need for effective monitoring of patients undergoing intravenous (IV) treatment. During the course of medical care, patients often receive vital fluids, medications, and nutrients through IV drips. However, the conventional manual monitoring of IV bags is prone to errors and inefficiencies, particularly in busy healthcare environments. To overcome these challenges, the proposed Smart IV bag monitoring system employs sensor technology and interfacing units to provide real-time monitoring and management of IV treatments. The system consists of smart sensors attached to IV bags, a centralized monitoring unit, and a user interface for healthcare professionals. The smart sensors continuously track parameters such as fluid level, flow rate, and temperature within the IV bag. The data collected by the sensors is transmitted wirelessly to the centralized monitoring unit using GSM module. The Smart IV Bag Monitoring System incorporates an automated mechanism to ensure timely replacement of empty IV bags and continuous patient care. When the system detects that the IV bag is empty, it initiates a notification process by sending a text message alarm to the patient. The purpose of this alarm is to prompt the patient to acknowledge the empty IV bag and take necessary action.

Ensuring the well-being of workers, particularly at the production line level, is a top priority for organizations across all industries. This concern is crucial not only for the workers’ prosperity but also for the organization’s overall success. In environments where working conditions are harsh, and employees face significant risks while performing their tasks, accidents are unfortunately common occurrences. To address this issue effectively, we propose implementing a monitoring system in factories. This system will allow us to closely observe key safety parameters in the workplace, providing valuable insights into the likelihood of accidents. Our solution involves utilizing the ESP8266 Wi-Fi chip-enabled microcontroller NodeMCU. The safety system design incorporates three essential sensors: a DHT sensor to monitor temperature and humidity, an ultrasonic sensor (HC-04), and a smoke sensor (MQ2). These sensors continuously monitor the work environment’s conditions and transmit the data to the IoT platform, a powerful cloud-based solution that facilitates real-time data monitoring from anywhere in the world.

The primary objective of this study is to compare the acoustic channel characteristics between direct and multipath models in shallow and deep-water environments. Moreover, the study delves into the influence of temperature and salinity on sound speed propagation and absorption. These factors are affected by various chemical compositions present in the underwater medium. The assessment of these effects is conducted for both shallow and deep-water scenarios. Lastly, comprehensive scrutiny and comparison of transmission losses have been conducted for both the direct and multipath models. The simulation results clearly demonstrate that the transmission losses in deep water for the multipath model are significantly higher than those in shallow water. This difference can be attributed to the increased pressure and sound reflections experienced in the deep-water environment. Each 1 ℃ decrease in temperature results in a 3.5 m/s increase in acoustic velocity when sound travels from the water's surface to the bottom. In contrast, deep water maintains a constant acoustic velocity of 1545 m/s regardless of changes in salinity. However, in shallow water, there are significant variations in acoustic velocity due to salinity changes. Comparing deep water to shallow water, there is a considerable attenuation reduction of 20 dB in deep water. Specifically, at lower frequencies (0–100 kHz), the transmission losses for direct paths in deep water are almost negligible. In contrast, for multipath transmission, there is an increase of 93%. In shallow water, the transmission loss increases by 66% for direct path models and as much as 97% for multipath models.

The Internet of Things (IoT) is a system of unified gadgets that can conversation data and operate in tandem thanks to the web. When it comes to the longevity of a network, smooth data production is crucial, and wireless sensor networks (WSN) play a key character in the IoT in this regard. Despite the IoT’s usefulness in many areas, it still faces obstacles in the form of security, energy, load balancing, and storage. Clustering and multi-hop routing are two methods used in the architecture of an IoT-assisted WSN to reduce energy consumption. This research therefore provides a novel effective hybrid optimization strategy for choosing cluster heads. In to adjust the white shark optimizer’s (WSO) stochastic behaviour while it seeks out food, the suggested method makes use of the whale optimization approach (WOA). The new HWSO was also tested against a group of contemporary meta-heuristic methods, such as the artificial optimizer (GTO), the coyote optimization algorithm (COA), and the original WSO. Finally, the proposed network is put through its paces by making use of NS-3.26’s extensive simulation features. Improvements in packet delivery ratio (PDR), latency, energy consumption, number of dead nodes, and longevity of the network may be shown in the simulation results.

Vaxallot seeks to implement a system to distribute vaccines across high-risk groups accounting for various parameters and prove to be superior to what conventional systems are capable of today. It is a Python flask-based tool backed by infrastructure and data resources from the Covid India central repository; all it needs is a single channel input and a single parameter of the value produced, and the algorithm will take care of the rest. Since it’s Python-based and has an active integration with google sheets, live value updating could be possible for the real-time output of the distribution. The novelty of the proposed mechanism is the unique priority index, a score that accounts for an array of factors associated with the pandemic and is computed for regions in question here; this makes way for better distribution of vaccines. The application has an exclusive segment centered on handling excess units, if any. Moreover, since the application is developed to suit the needs of dynamic demographics, any region can roll out this application for purposes they desire to serve the masses. Since it isn’t bound by a coronavirus, it can be used by the healthcare industry as they deem fit.