Processing System Research Articles

Quantitative skin surface hydration measurement by visible optical image processing: A pilot study.

Skin barrier function is significantly impacted by skin moisture. Most non-invasive evaluation techniques to measure skin surface hydration relying on its electrical properties, which are limited in scope and have unstable operations. Applying image processing for skin hydration assessment is uncommon, with an emphasis on skin-capacitive pictures and near-infrared images in general, which demand a certain spectrum. As a result, there is an increasing need for wide-area skin hydration evaluation and mapping. Thestudy aimsto propose a quantitative evaluation algorithmforskin surface hydrationfrom visible-light images. Threedeviceswere applied tomeasureskin hydration:skin image capturedevice and tworecognizedcommercialskindevices.A digital image processing system creates a new index, called GVR, to symbolize skin surface moisture. TheCLAHE algorithmwas appliedto enhance the contrast of skin image, andafter calculating it with the monochrome image,the skin reflectance imagewas segmented.The GVR was estimated using the values of the individual sites and the entire skin. The correlation coefficient between the three methods was examined using statistical analysis to assess the performance of GVR. Skin hydrationestimated from visible-light imagesis influenced by the entire facial structure in addition to specific areas.The electrical and visible image evaluations showed a strong association with a significant difference. It was discovered that reflecting measures from visible images provide a quick and efficient way to quantify the moisture of the skin's surface.

A 36-nW Electrocardiogram Anomaly Detector Based on a 1.5-bit Non-Feedback Delta Quantizer for Always-on Cardiac Monitoring.

An always-on electrocardiogram (ECG) anomaly detector (EAD) with ultra-low power (ULP) consumption is proposed for continuous cardiac monitoring applications. The detector is featured with a 1.5-bit non-feedback delta quantizer (DQ) based feature extractor, followed by a multiplier-less convolutional neural network (CNN) engine, which eliminates the traditional high-resolution analog-to-digital converter (ADC) in conventional signal processing systems. The DQ uses a computing-in-capacitor (CIC) subtractor to quantize the sample-to-sample difference of ECG signal into 1.5-bit ternary codes, which is insensitive to low-frequency baseline wandering. The subsequent event-driven classifier is composed of a low-complexity coarse detector and a systolic-array-based CNN engine for ECG anomaly detection. The DQ and the digital CNN are fabricated in 65-nm and 180-nm CMOS technology, respectively, and the two chips are integrated on board through wire bonding. The measured detection accuracy is 90.6% ∼ 91.3% when tested on the MIT-BIH arrhythmia database, identifying three different ECG anomalies. Operating at 1 V and 1.4 V power supplies for the DQ and the digital CNN, respectively, the measured long-term average power consumption of the core circuits is 36 nW, which makes the detector among those state-of-the-art always-on cardiac anomaly detection devices with the lowest power consumption.

Effect of a learning-based approach using the echo-signals obtained by a single-unit transducer on detection of breast tumors.

1566 Background: Breast cancer mortalities in the less developed countries are predicted to increase over the next decades mainly due to the low utilization rates of breast cancer screening programs. Additionally, studies have shown that the sensitivity and accuracy of breast self-examination in women are suboptimal. Therefore, it is important to develop a novel and affordable technology that can accurately detect small breast tumors in women. We have developed a deep learning-based echo- signal processing system that can detect breast tumors with high sensitivity and accuracy by merely obtaining ego-motion estimated echo-signals generated by a single-unit piezoelectric transducer system. Methods: We have prospectively collected echo-signals using a single-unit piezoelectric transducer system in 200 patients with breast tumors who underwent curative surgery at the Seoul National University Hospital and SMG-SNU Boramae Medical Center between Oct 2022 and Feb 2024. The data from the first 131 cases was used for the training and testing of the deep learning model with the ratio of 8:2, and the subsequent data from 69 cases was used for the external validation. We used ImageNet pre-trained ResNet50 model to train the deep learning model and adopted various data augmentation methods for model robustness. Five nested cross-validation was used to ensure the generalization performance. Results: The median age of the enrolled patients was 55 (IOR, 47-63) and 65 patients (32.5%) had non-palpable breast tumors. Nearly half of the patients (n=93, 46.5%) had tumors smaller than 2.0 cm in the largest dimension. Our deep learning algorithm showed outstanding performance with the area under the curve (AUC) of 0.914±0.022 and 0.964±0.011 for the image- and region-level, respectively, in the training and testing set (n=131). In the external validation set (n=69), the model demonstrated an AUC of 0.846±0.012 and 0.932±0.009 for the image- and region-level, respectively. As shown (Table), the accuracy, sensitivity, and specificity were substantially improved for the region-level analysis when compared with those of the image-level analysis. Conclusions: Using a prospectively collected data from 200 patients, we developed a highly accurate and robust deep learning model to detect breast tumors in women by processing echo-signals obtained by a single-unit piezoelectric transducer system. Our data indicate that deep learning approach based on low-volume echo signal can lead to a novel and affordable breast tumor screening strategy that can improve early breast cancer detection.[Table: see text]

Identification of Slovak Tourists’ Attitudes Towards Digitalization for Circular Economy and Waste Management

Abstract The research paper explores the perspectives of a chosen group of Slovak tourists on how digitization drives circular economy practices and promotes efficient waste management in tourism. The study involves data from 103 participants, who expressed their opinions on sustainability concepts like digitization, innovation, circular economy, and waste management in tourism, using a 5-point Likert scale. The research’s main objective is to understand sentiments and attitudes towards integrating digitization and innovation for sustainable practices in the tourism sector. The findings reveal differences in attitudes among respondents. Visual aids like box plots are utilized to help interpret the results and emphasize how factors like interest in new technologies impact respondents’ attitudes. Implementing digital technologies in tourism plays a key role in creating efficient waste management systems and reducing the environmental burden. Data tracking and processing systems enable detailed analysis of waste generation patterns, providing valuable information to optimize collection and recycling processes. Digital technologies contribute to the overall reduction of the impact of tourism on the environment through electronic reservations, intelligent transport systems and other innovative solutions. These initiatives increase waste management efficiency and minimise tourism’s negative ecological impact, contributing to more sustainable and ecologically responsible tourism.

The Frontal Lobe and Top-down Control of Attention

The concept of attention in cognitive science encompasses a bidirectional nature: bottom-up attention based on the salience of sensory stimuli, and top-down attention, which involves voluntary control over aspects such as intensity, allocation, selectivity, and duration. Top-down attention is believed to be primarily realized through the frontal lobes that monitor on-going information processing. This monitoring helps detect situations requiring intervention and manipulates lower-level information processing systems as a part of executive functions.

P‐161: Full‐in‐situ Imaging and Laser Processing System Supporting Detection and Removal of Defective Micro‐LED Dies During Mass Transfer

Micro‐LEDs have been hailed as the next‐generation display technology, with mass transfer being the key to achieving mass production of Micro‐LED displays. During the mass transfer process, it is crucial to identify and remove defective dies in order to ensure high yield and optimal display performance. In this paper, a novel in‐situ observation, imaging, and laser processing system is proposed, enabling online, in‐situ, and zero‐misalignment removal of faulty dies during the mass transfer process. This system holds great promise for significantly improving the efficiency of mass transfer and further driving the realization of mass production for Micro‐LED displays.

Характеристики обнаружения когерентной системы при рассогласовании квадратурных каналов

Introduction – The operation of an adaptive coherent detection system is considered. The structure of a processing device is presented, containing a series-connected shaper of quadrature signal components that convert high-frequency input radio signals to video frequency, an adaptive multi-channel coherent storage device with threshold devices. Goal – To study the influence of amplitude and phase mismatches of quadrature channel parameters, which are inevitable in practice, on the operation of an adaptive coherent detection system. Formulation of the problem – Determine the spectral-correlation characteristics of the processed signals when the parameters of the quadrature channels are mismatched. Assess the influence of amplitude and phase deviations of the parameters of quadrature channels on the characteristics of a coherent detection system. Method – The complex variable method is used, in which the input high-frequency signals are represented at the video frequency by a pair of complex conjugate real components, shifted in phase by ninety degrees. Results – A model of the processed signal is presented at the video frequency, taking into account possible mismatches in the parameters of quadrature channels in practice. Expressions are obtained and graphs of the spectral density of the complex signal are plotted separately for the amplitude and phase mismatch of the quadrature channels. It is shown that the mismatch of quadrature channels leads to the appearance in the spectrum of the output signal of phase detectors of a component at a frequency that is the mirror frequency of the signal, which leads to an increase in the probability of false detection. The results of calculations of the probability of false detection of a signal depending on the deviation of the transmission coefficients of the quadrature channels and the phase mismatch of the reference voltages of the quadrature channels are presented. Conclusion – The significant influence of amplitude and phase mismatches of the parameters of quadrature channels on the spectral-correlation characteristics of the complex signal is shown. The mismatch of the parameters of the quadrature channels leads to deterioration in the detection characteristics of the coherent processing system. The research methodology used allows us to develop requirements for the quality of tuning quadrature channels.

Influence of contact characteristics of joint surface on vibration performance of the giant magnetostrictive transducer

The giant magnetostrictive transducer is a transducer device that realizes magneto-mechanical energy conversion. Each mechanical component is connected by the joint surface to realize the transmission of ultrasonic vibration energy. To ensure the efficient transmission of energy, the influence of the contact characteristics of the joint surface on the output stability of the transducer is studied. According to the contact conditions between the mechanical joint surfaces of the giant magnetostrictive ultrasonic transducer (GMUT), the key factors affecting the mechanical vibration performance of the ultrasonic system are obtained by analyzing the vibration transmission characteristics of the joint surfaces. The influence of different joint surface contact characteristics (JSCT) on the amplitude–frequency curve of the transducer is analyzed by the ANSYS software. Simulations and experiments have been conducted to verify the predicted results. As the preload force increases, the natural frequency of the transducer increases, but the growth rate decreases. The natural frequency of the double-rod GMUT with a small joint surface area is slightly higher in the optimal output mode shape, while its amplitude is significantly larger. The optimal prestress for the GMUT with different-sized joint surfaces is 3–5 MPa. This paper acquires the JSCT under a high-frequency vibration condition, reveals the influence of the joint surface on the mechanical output performance of the GMUT, and can provide a theoretical basis for the design and analysis of the rotary ultrasonic vibration processing system.

The development of information processing systems for forests and forest resources

Information systems are applied in the forestry sector to address a wide range of tasks. The process of their development has led to the emergence of a heterogeneous set of systems and methods. The aim of the research is to determine their further development and formulate a work plan. To achieve this, the author conducted a review of publications on the subject, including both theoretical works and existing systems and processing methods. The guiding principle of selection was to provide a comprehensive and thorough coverage of the subject area. The methods were classified according to the tasks they solve and presented in logical order, starting from the widely used ones and ending with experimental ones. As a result, it was found that analytical methods are developing significantly, which will lead to the emergence of new data models in the future. Geographic information systems, specifically distributed network-based ones, are also evolving. The problem of modeling forest vegetation is generally part of the task of modeling ecosystems as a whole. The author concluded that integrated information systems are a relevant direction for the industry. A project for further development was proposed, decomposing the task of building information systems. The author sees the forest inventory system as the main system, upon which all other systems depend and can be presented as separate services. The research contributes to the development of theoretical concepts of forest information processing systems. It is useful for specialists and researchers in the field of forestry, as well as developers of specialized software.

Abstraction and decision fusion architecture for resource-aware image understanding with application on handwriting character classification

Resource-aware image understanding aims to achieve a soft equilibrium by effectively managing the constraints imposed by computational resources while improving the inferential capabilities of image processing systems. It serves a broad range of applications, spanning from embedded systems and IoT devices to budget-friendly smartphones and tablets. The proposed Abstraction and Decision Fusion Architecture (ADFA) addresses this problem through three tiers: abstraction, computation, and decision fusion. The first tier contains various views to generate different abstractions from the original data. These views are processed independently by an array of lightweight models forming the computation tier. They make independent decisions, where the final output is produced using a decision fusion tool in the last tier. To assess the capability of the proposed architecture, we have developed several ADFA-based models for the classification of handwriting data. In this regard, we first defined three data abstractions. Then, we trained support vector machines and fully connected neural networks according to the abstractions, which led to a set of independent basic models. Finally, an adaptive neuro-fuzzy inference system is employed as their hub to increase the accuracy by performing the decision fusion. Our experiments on the EMNIST dataset verify the efficiency and high accuracy of the proposed architecture in recognizing handwritten data, where the model size and the number of Multiply-Accumulate (MAC) operations are significantly smaller than state-of-the-art computational models.

Implementasi Structured System Analysis and Design Method pada Sistem Informasi Retribusi Pasar

Mojopanggung market is a traditional market located in mojopanggung sub-district, giri sub-district, banyuwangi regency. Based on the field survey, there are problems with the data processing system for market retribution income reports managed by market treasurers who stell have a conventional approach in processing payment data recorded in books and microsoft excel. This results in the current system having many weaknesses and limitations, increasing the risk of data loss. In addition, providing information to recapitulation officers in the field of market management becomes difficult. Therefore, it is necessary to design a website-based market levy income information system, which can handle problems that arise, where the system can be used to monitor market levy income report data, as well as facilitate the provision of information to recapitulation officers in the field of market management the design of a website-based market levy income information system was built by applying the structured system analysis and design method (SSADM). From the results of research that has been carried out, every company or government agency is encouraged to utilize information technology as a means of supporting business activities. A part from that, designing a website-based market levy income information system is very necessary and needed, in order to make it easier to provide information related to market traders’ dependents, as well as reporting levy income results and activities for monitoring data, so that in can produce levy income report data more easily and effectively

Technical Guidance on The Integration of Cattle and Food Crops in Sindang Kasih Village, South Konawe District

This technical guidance aims to provide understanding to cattle breeders regarding the benefits of integrating cattle and food crops in one area so that participants are motivated and encouraged to carry out integration between cattle and food crops. This technical guidance was implemented at Sindang Kasih Village, West Ranomeeto District. Implementation of technical guidance uses lecture and discussion methods. The tools and materials used are vehicles, cell phones, and laptops. In general, Cattle Farmers in Sindang Kasih Village already understand the integration of cattle and food crops and its benefits and are committed to implementing this integration as indicated by the ability of all participants to answer questions correctly at the end of the activity session (100%). The challenges and problems of beef cattle farming include maintenance and waste processing systems. Integrating livestock with food crops in Sindang Kasih Village has been implemented well. The livestock in Sindang Kasih needs to be further improved to become one of the breeding and fattening centers in Southeast Sulawesi.

Acoustic dynamics in performance halls: Enhancing violin sound quality in the FPSD orchestra room

With an emphasis on improving violin sound quality, this study explores the acoustic dynamics of the FPSD Orchestra Room at Universitas Pendidikan Indonesia. Direct and reflected sound are the two factors that impact the phenomena of interior sound. This research emphasizes the crucial balance between sound absorption and reflection to optimize the acoustic environment and ensure clarity and richness in violin performances. Improving acoustic conditions is vital to increase audience experience and performance quality. The study used a qualitative descriptive research style combining literature review and observations. The research site was the FPSD Orchestra Room, renowned for its historical significance and contribution to music education. The observations revealed significant acoustic obstacles that adversely affected the violin sound's clarity, including excessive reverberation and unequal sound dispersion. The literature review revealed the theoretical underpinnings of sound propagation, reverberation, absorption, reflection, and diffraction. The acoustic environment can be greatly enhanced by introducing sound-absorbing materials to optimize reverberation duration, controlling reflections with diffusers, and utilizing adaptive acoustic systems. Furthermore, combining virtual acoustics technology with digital sound processing systems allows for dynamic control over acoustic parameters, increasing the performance space's adaptability. These improvements provide a customized acoustic environment that supports a variety of musical performances and guarantees the audience a clear, engaging auditory experience. This study emphasizes the significance of fusing cutting-edge technology innovations with conventional acoustic design concepts to attain optimal sound quality in performance halls. Innovation and research must never stop to improve these acoustic settings even further.

Artificial Intelligence: A Quick Overview of Speech Recognition System

Abstract: The study of intelligent behaviour is known as artificial intelligence. Wagner said, "We build intelligent machines in science." By this, he implied that the primary goal is to teach these sophisticated devices, such as computers, to examine and comprehend human conduct. numerous believed that human intelligence might be understood through the construction of several programmes, while other researchers believed that numerous basics should be required in order to accomplish the intended objective. We can carry out or replicate any type of task we conduct using a computer. Therefore, computers are the ideal devices for developing artificial intelligence. In the hopes that they will outperform computers in several other areas, some researchers created additional computing devices. Billions of dollars were invested in creating new devices that surpassed the speed of the computer used to simulate software. However, the computers and the code both need to be extremely quick. As you learn about artificial intelligence, you may wonder, what really is intelligence? How is intelligence measured? Turn become something quite significant. In this case, the programme that evaluates its surroundings acts as the intelligent agent. Modern digital computers and human minds are comparable to one other in ways such as symbolic information processing systems. Both use symbolic data as input, change it in accordance with predetermined guidelines, and then use the results to solve issues. In order to mechanically replicate intelligent human activity, artificial intelligence researchers have programmed some algorithms to recognise intelligent human behaviour. Human conduct in language processing, chess, and other games, as well as medical diagnostics, may be used to monitor this activity. Voice recognition is a key component of AI. A certain voice may be recognised using voice recognition technology. The cornerstone for speaker identification is voice signals. Voice targeting is applicable to a wide range of applications, including voice mail, database access, phone banking, and phone purchasing. The ability to enter one's voice for verification is among the most potent uses of voice recognition for security. The fundamental means of interpersonal communication is speech. The technique of translating voice sounds into appropriate text is known as speech recognition. Over the past few years, speech recognition technology has advanced significantly. Nonetheless, there are other significant study obstacles, such as variations in speaker and language, ambient sound, word size, etc. This study aims to give a comprehensive overview of speech acceptance by summarising the several approaches utilised in the standard speech system and describing the numerous processes involved

Overview of Advanced Liquid Process System: Circulation of tritiated water in oceanic environment

The recent Japanese disposal of Advanced Liquid Processing System (ALPS)-treated water is controversial. ALPS does not filter tritium. The objectives of this paper are (a) to examine how anthropogenic tritium triggers biological health impacts and (b) to review the circulation of tritiated water into the oceanic territory of the Republic of Korea. I reviewed the possibility of the bioaccumulation of tritium in the oceanic environment and its overall health impact. To be of significant status, they require complex conditions. I also reviewed the simulation of the possible path that disposed pollutants will take from Fukushima. The simulation was then compared with the measured level of radionuclides around the Republic of Korea's oceanic territory by year. The data is divided into three parts (east, west, and south) and analyzed to check if the trends show any patterns in the level of tritium in the Republic of Korea. The levels checked in three areas showed a partial uniformity, which may be evidence that radionuclides entered the oceanic territory of the Republic of Korea. However, the level of tritium was extremely low compared to the regulations set by the World Health Organization and the Republic of Korea. Thus, the disposal of tritium will be less likely to affect the natural environment. Nevertheless, it is recommended to monitor disposed tritium by a third party, plan for compensation, and conduct intense research on the circulation of tritium to support the prevention of sudden failure of the emission system.

BlockEdge: Building Bridges to Safe and Efficient Distributed Systems

Abstract: In the ever-evolving landscape of distributed systems, ensuring safety, efficiency, and scalability remains a paramount challenge. BlockEdge emerges as a pioneering framework designed to address these critical issues by leveraging the principles of blockchain technology and advanced consensus mechanisms. This abstract outlines the key features, innovations, and potential impacts of BlockEdge on the realm of distributed computing. BlockEdge integrates blockchain's immutable ledger properties with a novel consensus algorithm tailored for distributed systems. Unlike traditional blockchain applications that prioritize decentralization for financial transactions, BlockEdge focuses on enhancing the performance and reliability of distributed applications. The framework employs a hybrid consensus model that combines Byzantine Fault Tolerance (BFT) with Proof-of-Stake (PoS), optimizing both security and energy efficiency. A standout feature of BlockEdge is its modular architecture, which allows seamless interoperability between different types of distributed networks. This modularity facilitates the integration of various consensus protocols, catering to the specific needs of diverse applications, from IoT networks to large-scale data processing systems. By enabling secure and efficient cross-chain communication, BlockEdge effectively mitigates the silo effect prevalent in current distributed system designs.

Responsiveness and Precision of Digital IMUs under Linear and Curvilinear Motion Conditions for Local Navigation and Positioning in Advanced Smart Mobility.

Sensors based on MEMS technology, in particular Inertial Measurement Units (IMUs), when installed on vehicles, provide a real-time full estimation of vehicles' state vector (e.g., position, velocity, yaw angle, angular rate, acceleration), which is required for the planning and control of cars' trajectories, as well as managing the in-car local navigation and positioning tasks. Moreover, data provided by the IMUs, integrated with the data of multiple inputs from other sensing systems (such as Lidar, cameras, and GPS) within the vehicle, and with the surrounding information exchanged in real time (vehicle to vehicle, vehicle to infrastructure, or vehicle to other entities), can be exploited to actualize the full implementation of "smart mobility" on a large scale. On the other hand, "smart mobility" (which is expected to improve road safety, reduce traffic congestion and environmental burden, and enhance the sustainability of mobility as a whole), to be safe and functional on a large scale, should be supported by highly accurate and trustworthy technologies based on precise and reliable sensors and systems. It is known that the accuracy and precision of data supplied by appropriately in-lab-calibrated IMUs (with respect to the primary or secondary standard in order to provide traceability to the International System of Units) allow guaranteeing high quality, reliable information managed by processing systems, since they are reproducible, repeatable, and traceable. In this work, the effective responsiveness and the related precision of digital IMUs, under sinusoidal linear and curvilinear motion conditions at 5 Hz, 10 Hz, and 20 Hz, are investigated on the basis of metrological approaches in laboratory standard conditions only. As a first step, in-lab calibrations allow one to reduce the variables of uncontrolled boundary conditions (e.g., occurring in vehicles in on-site tests) in order to identify the IMUs' sensitivity in a stable and reproducible environment. For this purpose, a new calibration system, based on an oscillating rotating table was developed to reproduce the dynamic conditions of use in the field, and the results are compared with calibration data obtained on linear calibration benches.

The evolution of AI: What does the future hold in the next two years

Artificial intelligence (AI) has evolved rapidly in recent years, transforming several industries and reshaping cultural norms. This article examines the current state of AI technology, focusing on significant trends and developments that have accelerated its growth. This paper sheds light on the evolving environment of AI innovation by examining current breakthroughs in machine learning, deep learning, and ethical concerns surrounding AI deployment. The following two years should see substantial advances in natural language processing, computer vision, and autonomous systems. Despite the excitement, difficulties such as ethical considerations, regulatory frameworks, and societal repercussions loom large, needing careful study and decisive action. This study aims to inform stakeholders about the transformative potential of AI and the methods required to properly navigate its growing landscape by conducting a balanced examination of opportunities and challenges.

Thermal analysis of hybrid nanoliquid contains iron-oxide (Fe3O4) and copper (Cu) nanoparticles in an enclosure

The major aim of this work is to analyze the thermophysical properties of hybrid nanoliquid inside a square lid driven enclosure under the effect of applied magnetic field and mixed convection. The Hybrid nanofluid is considered a suspension of Iron-oxide (Fe3O4) and Copper (Cu) nanoparticles into water. The cavity walls have varying properties such as top adiabatic wall is moving continuously while the lower wall is maintained at a high constant temperature, in addition, the vertical walls are kept at a low fixed temperature. The magnetic field is applied to the right vertical wall in a horizontal direction. Additionally, the effects of buoyancy forces caused by temperature gradients and shear forces caused by continuous lid motion are considered. The mathematical modelling of problem with all assumptions yields the nonlinear partial differential system. First this system is transferred into non-dimensional form and then transformed system is solved by using Galerkin finite element method (GFEM) along with Gaussian elimination method. Results for isotherms, streamlines and average Nusselt number are obtained versus Richardson number (0.1 ≤ Ri ≤ 15), Grashof number (10 ≤ Gr ≤ 10000), Hartmann number (0 ≤ Ha ≤ 100), volume fractions of solid nanoparticles (0.005 ≤ ϕ1 ≤ 0.02) and (0.005 ≤ ϕ2 ≤ 0.02). It is observed that the Richardson number and Grashof number have significant impacts on both flow velocity and temperature. In addition, concentration of hybrid nanoparticles improves the heat transfer performance. The obtained results may be crucial for thermal management in the cooling of electronics, heat exchangers, solar thermal collectors, industrial operations, medical equipment, HVAC systems, food processing, and renewable energy systems.

Role and integration of image processing systems for maritime target tracking

In recent years, maritime traffic has increased, especially in seaborne trade. To ensure safety, security, and environmental protection, various systems have been deployed, often combining data for improved effectiveness. One key application of this combined data is tracking targets at sea, where the Automatic Identification System (AIS) and X-band marine radar are crucial. Recently, there has been growing interest in using visual data from cameras to enhance tracking. This has led to the development of several tracking algorithms based on image processing. While much of the existing literature addresses data fusion, there hasn’t been much focus on why integrating image processing systems is important given the existence of the other systems. In our paper, we aim to analyze these surveillance systems and highlight the benefits of integrating image processing systems. Our main goal is to show how this integration can improve maritime security, offering practical insights into enhancing safety and protection at sea.