Iraqi Population Trusts in Electronic Healthcare Records: A Cross-sectional Study.

This study investigated the perceptions of Iraqi patients regarding Electronic Healthcare Records (EHRs) in terms of trust and propensity to share and exchange medical and personal information and data within the healthcare ecosystem. During the period of April to June 2022, a researcher-assisted questionnaire was disseminated to adult Iraqi patients attending public or private healthcare facilities in a subset of Iraqi governorates. Data collection was followed by descriptive and inferential analyses. In total, 552 respondents filled out the questionnaire. The findings revealed that 71.6% of respondents were conversant with EHRs and trusted them as data collection and storage systems. In addition, 10% of respondents did not want their EHRs to be shared between healthcare professionals and institutions. However, only 3.6% of participants were willing to share all of their personal information with healthcare professionals. Female respondents were considerably more willing to share their full names with healthcare professionals than male respondents, despite the society's reputation for conservatism. The findings of this study highlighted the necessity of tailoring initiatives to enhance patients' trust in EHRs and their interactions with healthcare professionals other than medical physicians.

Knowledge and practices of radiation protection among Malaysian radiographers working in nuclear medicine: A preliminary study.

This study is aimed to determine knowledge and practices on radiation protection among radiographers in nuclear medicine department. A cross-sectional survey was conducted among radiographers in nuclear medicine departments in four health institutions in Malaysia. A set of questionnaires was distributed to 17 respondents using convenience sampling. Approximately more than 75% and 44% - 56% of the radiographers have good knowledge of radiation protection and frequent adherence to radiation protection practices, respectively. Levels of education and length of service were statistically correlated with radiation protection knowledge and practices attributes (p < 0.05), respectively. More training is necessary for knowledge and practice improvement.

A Case Series on a Rare Gynecological Cancer and a Review of Recent Literature on Vulval Cancer.

Vulval cancer is a rare gynaecological malignancy. Though it has got excellent prognosis if diagnosed and treated early, but in most instances, women present late with advanced disease as they are too uncomfortable to discuss it with their doctors. Advanced vulval cancer is difficult to treat, has got poor prognosis and the treatment itself can cause morbidity and mortality. The authors describe three cases of isolated vulval cancer in a gynaecology centre in south Wales that had late presentation due to embarrassment despite noticing the lesion for long time and a brief review of the literature on its prevalence, clinical presentation, investigation and best management.

DIETARY LIFESTYLE, HYPOALBUMINAEMIA AND ANAEMIA AMONG OLDER ADULTS ATTENDING A PRIMARY CARE CLINIC IN NIGERIA: A CROSS-SECTIONAL STUDY.

Introduction: Anaemia has been extensively studied in children and women of reproductive age. However, there are few data on anaemia and related conditions in the elderly from developing countries. Objectives: To determine the prevalence and severity pattern of anaemia, and assess the relationship between dietary lifestyle, hypoalbuminaemia, and anaemia in older persons. Methodology: A cross-sectional study involving 378 patients aged≥60 years who presented at the General Outpatient Clinic. Dietary lifestyle was assessed using a structured questionnaire. Samples were collected for packed cell volume and serum albumin. Inferential statistical analyses were used to determine the associations between variables. Results: A total of 348 respondents completed the study. The mean age of respondents was 67.83 ±7.53 years with female (60.9%) predominance. The prevalence of anaemia and hypoalbuminaemia were 42.2% and 17.8% respectively. Hypoalbuminaemia (ß=0.335, 95%CI=0.131-0.229, P<0.001), long duration of co-morbidities (ß= - 0.179, 95%CI= -0.165-0.047, P<0.001), one full meal/day (ß=0.130, 95%CI=0.224-1.879, P=0.013), and low monthly income (ß=0.122, 95%CI=0.179-1.543, P=0.026) were the predictors of anaemia among the elderly in this study. Conclusion: Data on the predictors of anaemia from this study will be useful in developing guidelines and strategies for managing the condition in primary care settings and other similar sites.

Visual Cues for a Steadier You: Visual Feedback Methods Improved Standing Balance in Virtual Reality for People with Balance Impairments.

Users of head-mounted displays (HMDs) for virtual reality (VR) sometimes have balance issues since HMDs impede their view of the outside world. This has a greater impact on people with balance impairments since many rely more heavily on their visual cues to keep their balance. This is a significant obstacle to the universal usability and accessibility of VR. Although previous studies have verified the imbalance issue, not much work has been done to diminish it. In this study, we investigated how to increase VR balance by utilizing additional visual cues. To examine how different visual approaches (static, rhythmic, spatial, and center of pressure (CoP) based feedback) affect balance in VR, we recruited 100 people (50 with balance impairments due to multiple sclerosis and 50 without balance impairments) across two different geographic locations (United States and Bangladesh). All people completed both standing visual exploration as well as standing reach and grasp tasks. Results demonstrated that static, rhythmic, and CoP visual feedback approaches enhanced balance significantly ( ) in VR for people with balance impairments. The methods described in this study could be applied to design more accessible virtual environments for people with balance impairments.

Hanging: Commonly Encountered by Forensic Experts at Autopsy.

Though human lives have become easier and faster due to rapid twist in urbanization, industrialization and digitalization suicidal tendency among common people are often seen. Hanging is the commonly chosen method to do so. The study was designed to find out the pattern of hanging cases and to discover the immensity of hanging as a method of committing suicide. This retrospective study was done for three years by retrospectively collected data at the department of Forensic Medicine and Toxicology of Chattogram Medical College. A total of 193 cases (6.73%) of hanging were observed among 2850 autopsies done from January 2015 to December 2017. The age group of 31-40 years was mostly affected i.e. in 54(27.97%) followed by 21-30 years 48(24.87%). Males 112(58.03%) out numbered the females 81(41.96%). Clothes 88(45.59%) were mostly used as ligature material followed by jute rope (33.67%) and nylon rope (20.72%). Maximum cases were atypical hanging 160(82.90%), while we observed 33 typical (17.09%) hangings. In 166 cases (86.01%) we observed no injuries to the neck while contusion of the neck in 27 cases (13.99%). This study revealed fracture of the thyroid cartilage in 5 cases (2.59%) and hyoid in 2 cases (1.03%). One hundred & eighty five (185) cases (95.85%) were of suicidal and only 8 cases (4.14%) were of accidental. As per observation of this study, hanging has been found to be a common means of committing suicide in Bangladesh.

Conventional and advanced detection techniques of foodborne pathogens: A comprehensive review.

Foodborne pathogens are a major public health concern and have a significant economic impact globally. From harvesting to consumption stages, food is generally contaminated by viruses, parasites, and bacteria, which causes foodborne diseases such as hemorrhagic colitis, hemolytic uremic syndrome (HUS), typhoid, acute, gastroenteritis, diarrhea, and thrombotic thrombocytopenic purpura (TTP). Hence, early detection of foodborne pathogenic microbes is essential to ensure a safe food supply and to prevent foodborne diseases. The identification of foodborne pathogens is associated with conventional (e.g., culture-based, biochemical test-based, immunological-based, and nucleic acid-based methods) and advances (e.g., hybridization-based, array-based, spectroscopy-based, and biosensor-based process) techniques. For industrial food applications, detection methods could meet parameters such as accuracy level, efficiency, quickness, specificity, sensitivity, and non-labor intensive. This review provides an overview of conventional and advanced techniques used to detect foodborne pathogens over the years. Therefore, the scientific community, policymakers, and food and agriculture industries can choose an appropriate method for better results.

Comparative study and multi-parameter analysis to optimize device structure of triboelectric nanogenerators.

Triboelectric nanogenerator is becoming one of the most efficient energy harvesting device among all mechanical energy harvesters. This device consists of dielectric friction layers and metal electrode which generates electrical charges using electrostatic induction effect. There are several factors influencing the performance of this generator which needs to be evaluated prior to experiment. The absence of a universal technique for TENG simulation makes the device design and optimization hard before practical fabrication, which also lengthens the exploration and advancement cycle and hinders the arrival of practical applications. In order to deepen the understanding the core physic behind the working process of this device, this work will provide comparative analysis on different modes of TENG. Systematic investigation on different material combination, effect of material thickness, dielectric constant and impact of surface patterning is evaluated to shortlist the best material combination. COMSOL Multiphysics simulating environment is used to design, model and analyze factor affecting the overall output performance of TENG. The stationary study in this simulator is performed using 2D geometry structure with higher mesh density. During this study short circuit and open circuit condition were applied to observe the behavior of charge and electric potential produced. This observation is analyzed by plotting charge transfer/electric potential against various displacement distances of dielectric friction layers. The ouput is then provided to load ciruitary to measure the maximum output power of the models. Overall, this study provides an excellent understanding and multi-parameter analysis on basic theoretical and simulation modeling of TENG device.

Evaluating fundamental biochar properties in relation to water holding capacity.

Biochar products that hold and release water within a stable carbonised porous structure provide many opportunities for climate mitigation and a range of applications such as for soil amendments. Biochar that are produced from various organic feedstocks by pyrolysis can provide multiple co-benefits to soil including improving soil health and productivity, pH buffering, contaminant control, nutrient storage, and release, however, there are also risks for biochar application in soils. This study evaluated fundamental biochar properties that influence Water Holding Capacity (WHC) of biochar products and provides recommendations for testing and optimising biochar products prior to soil applications. A total of 21 biochar samples (locally sourced, commercially available, and standard biochars) were characterised for particle properties, salinity, pH and ash content, porosity, and surface area (with N2 as adsorbate), surface SEM imaging, and several water testing methods. Biochar products with mixed particle size, irregular shapes, and hydrophilic properties were able to rapidly store relatively large volumes of water (up to 400% wt.). In contrast, relatively less water (as low as 78% wt.) was taken up by small-sized biochar products with smooth surfaces, along with hydrophobic biochars that were identified by the water drop penetration test (rather than contact angle test). Water was stored mostly in interpore spaces (between biochar particles) although intra-pore spaces (meso-pore and micropore scale) were also significant for some biochars. The type of organic feedstock did not appear to directly affect water holding, although further work is needed to evaluate mesopore scale processes and pyrolytic conditions that could influence the biochemical and hydrological behaviour of biochar. Biochars with high salinity, and carbon structures that are not alkaline pose potential risks when used as soil amendments.

Utilization of telehealth services in low- and middle-income countries amid the COVID-19 pandemic: a narrative summary.

BACKGROUND: During the current period of the pandemic, telehealth has been a boon to the healthcare system by providing quality healthcare services at a safe social distance. However, there has been slow progress in telehealth services in low- and middle-income countries with little to no evidence of the cost and effectiveness of such programmes. OBJECTIVE: To provide an overview of the expansion of telehealth in low- and middle-income countries amid the COVID-19 pandemic and identify the challenges, benefits, and costs associated with implementing telehealth services in these countries. METHODS: We performed a literature review using the search term: '*country name* AND ((telemedicine[Title][Abstract]) OR (telehealth[Title][Abstract] OR eHealth[Title][Abstract] OR mHealth[Title][Abstract]))'. Initially, we started with 467 articles, which were reduced to 140 after filtering out duplicates and including only primary research studies. Next, these articles were screened based on established inclusion criteria and 44 articles were finalised to be used in the review. RESULTS: We found telehealth-specific software being used as the most common tool to provide such services. Nine articles reported patient satisfaction of greater than 90% with telehealth services. Moreover, the articles identified the ability to make a correct diagnosis to resolve the condition, efficient mobilisation of healthcare resources, increased accessibility for patients, increased service utilisation, and increased satisfaction as benefits of telehealth services, whereas inaccessibility, low technological literacy, and lack of support, poor security standards and technological concerns, loss of interest by the patients, and income impacts on physicians as challenges. The review could not find articles that explored the financial information on telehealth programme implementation. CONCLUSION: Although telehealth services are growing in popularity, the research gap on the efficacy of telehealth is high in low- and middle-income countries. To better guide the future development of telehealth services, rigorous economic evaluation of telehealth is needed.

Advanced triboelectric nanogenerator-driven drug delivery systems for targeted therapies.

In the current decade, remarkable efforts have been made to develop a self-regulated, on-demand and controlled release drug delivery system driven by triboelectric nanogenerators (TENGs). TENGs have great potential to convert biomechanical energy into electricity and are suitable candidates for self-powered drug delivery systems (DDSs) with exciting features such as small size, easy fabrication, biocompatible, high power output and economical. This review exclusively explains the development and implementation process of TENG-mediated, self-regulated, on-demand and targeted DDSs. It also highlights the recently used TENG-driven DDSs for cancer therapy, infected wounds healing, tissue regeneration and many other chronic disorders. Moreover, it summarises the crucial challenges that are needed to be addressed for their universal applications. Finally, a roadmap to advance the TENG-based drug delivery system developments is depicted for the targeted therapies and personalised healthcare.

Optimising water holding capacity and hydrophobicity of biochar for soil amendment - A review.

Biochar is a product of the thermal treatment of biomass, and it can be used for enhancing soil health and productivity, soil carbon sequestration, absorbance of pollutants from water and soil, and promoting environmental sustainability. Extensive research has been done on applications of biochar to enhance the Water Holding Capacity (WHC) of biochar amended soil. However, a comprehensive road map of biochar optimised for enhanced WHC, and reduced hydrophobicity is not yet published. This review is the first to provide not only quantitative information on the impacts of biochar properties in WHC and hydrophobicity, but also a road map to optimise biochar for enhanced WHC when applied as a soil amendment. The review shows that straw or grass-derived biochar (at 500-600 °C) increases the WHC of soil if applied at 1 to 3 % in the soil. It is clear from the review that soil of varying texture requires different particle sizes of biochar to enhance the WHC and reduce hydrophobicity. Furthermore, the review concludes that ageing biochar for at least a year with enhanced oxidation is recommended for improving the WHC and reducing hydrophobicity compared to using biochar immediately after production. Additionally, while producing biochar a residence time of 1 to 2 h is recommended to reduce the biochar's hydrophobicity. Finally, a road map for optimising biochar is presented as a schematic that can be a resource for making decisions during biochar production for soil amendment.

Recent advancements in bioelectronic devices to interface with the peripheral vestibular system.

Balance disorders affect approximately 30% of the population throughout their lives and result in debilitating symptoms, such as spontaneous vertigo, nystagmus, and oscillopsia. The main cause of balance disorders is peripheral vestibular dysfunction, which may occur as a result of hair cell loss, neural dysfunction, or mechanical (and morphological) abnormality. The most common cause of vestibular dysfunction is arguably vestibular hair cell damage, which can result from an array of factors, such as ototoxicity, trauma, genetics, and ageing. One promising therapy is the vestibular prosthesis, which leverages the success of the cochlear implant, and endeavours to electrically integrate the primary vestibular afferents with the vestibular scene. Other translational approaches of interest include stem cell regeneration and gene therapies, which aim to restore or modify inner ear receptor function. However, both of these techniques are in their infancy and are currently undergoing further characterization and development in the laboratory, using animal models. Another promising translational avenue to treating vestibular hair cell dysfunction is the potential development of artificial biocompatible hair cell sensors, aiming to replicate functional hair cells and generate synthetic 'receptor potentials' for sensory coding of vestibular stimuli to the brain. Recently, artificial hair cell sensors have demonstrated significant promise, with improvements in their output, such as sensitivity and frequency selectivity. This article reviews the history and current state of bioelectronic devices to interface with the labyrinth, spanning the vestibular implant and artificial hair cell sensors.

A Smart Camera Trap for Detection of Endotherms and Ectotherms.

Current camera traps use passive infrared triggers; therefore, they only capture images when animals have a substantially different surface body temperature than the background. Endothermic animals, such as mammals and birds, provide adequate temperature contrast to trigger cameras, while ectothermic animals, such as amphibians, reptiles, and invertebrates, do not. Therefore, a camera trap that is capable of monitoring ectotherms can expand the capacity of ecological research on ectothermic animals. This study presents the design, development, and evaluation of a solar-powered and artificial-intelligence-assisted camera trap system with the ability to monitor both endothermic and ectothermic animals. The system is developed using a central processing unit, integrated graphics processing unit, camera, infrared light, flash drive, printed circuit board, solar panel, battery, microphone, GPS receiver, temperature/humidity sensor, light sensor, and other customized circuitry. It continuously monitors image frames using a motion detection algorithm and commences recording when a moving animal is detected during the day or night. Field trials demonstrate that this system successfully recorded a high number of animals. Lab testing using artificially generated motion demonstrated that the system successfully recorded within video frames at a high accuracy of 0.99, providing an optimized peak power consumption of 5.208 W. No water or dust entered the cases during field trials. A total of 27 cameras saved 85,870 video segments during field trials, of which 423 video segments successfully recorded ectothermic animals (reptiles, amphibians, and arthropods). This newly developed camera trap will benefit wildlife biologists, as it successfully monitors both endothermic and ectothermic animals.

Advancements in Algorithms and Neuromorphic Hardware for Spiking Neural Networks.

Artificial neural networks (ANNs) have experienced a rapid advancement for their success in various application domains, including autonomous driving and drone vision. Researchers have been improving the performance efficiency and computational requirement of ANNs inspired by the mechanisms of the biological brain. Spiking neural networks (SNNs) provide a power-efficient and brain-inspired computing paradigm for machine learning applications. However, evaluating large-scale SNNs on classical von Neumann architectures (central processing units/graphics processing units) demands a high amount of power and time. Therefore, hardware designers have developed neuromorphic platforms to execute SNNs in and approach that combines fast processing and low power consumption. Recently, field-programmable gate arrays (FPGAs) have been considered promising candidates for implementing neuromorphic solutions due to their varied advantages, such as higher flexibility, shorter design, and excellent stability. This review aims to describe recent advances in SNNs and the neuromorphic hardware platforms (digital, analog, hybrid, and FPGA based) suitable for their implementation. We present that biological background of SNN learning, such as neuron models and information encoding techniques, followed by a categorization of SNN training. In addition, we describe state-of-the-art SNN simulators. Furthermore, we review and present FPGA-based hardware implementation of SNNs. Finally, we discuss some future directions for research in this field.

New alternatives from sustainable sources to wheat in bakery foods: Science, technology, and challenges.

Ongoing research in the food industry is striving to replace wheat flour with new alternatives from sustainable sources to overcome the disease burden in the existing population. Celiac disease, wheat allergy, gluten sensitivity, or non-celiac gluten sensitivity are some common disorders associated with gluten present in wheat. These scientific findings are crucial to finding appropriate alternatives in introducing new ingredients supporting the consumer's requirements. Among the alternatives, amaranth, barley, coconut, chestnut, maize, millet, teff, oat, rye, sorghum, soy, rice flour, and legumes could be considered appropriate due to their chemical composition, bioactive profile, and alternatives utilization in the baking industry. Furthermore, the enrichment of these alternatives with proper ingredients is considered effective. Literature demonstrated that the flours from these alternative sources significantly enhanced the physicochemical, pasting, and rheological properties of the doughs. These flours boost a significant reduction in gluten proteins associated with food intolerance, in comparison with wheat highlighting a visible market opportunity with nutritional and organoleptic benefits for food producers. PRACTICAL APPLICATIONS: New alternatives from sustainable sources to wheat in bakery foods as an approach that affects human health. Alternatives from sustainable sources are important source of nutrients and bioactive compounds. Alternatives from sustainable sources are rising due to nutritional and consumer demand in bakery industry. New alternatives from sustainable sources improve physicochemical, pasting, and rheological properties of dough. Non-wheat-based foods from non-traditional grains have a potential to increase consumer market acceptance.

A Win-Win for Sport and Exercise Medicine and Primary Care: A Qualitative Case Study of the Added Competence Model in Canada.

OBJECTIVE: To understand the unique impacts of the College of Family Physicians of Canada's (CFPC) Certificate of Added Competence (CAC) in Sport and Exercise Medicine (SEM) on the delivery of comprehensive care in Canada. DESIGN: Secondary analysis of qualitative interview data collected during a multiple case study of the impacts of the CAC program in Canada. SETTING: Six cases purposively sampled from across Canada. Each case was bound by a collective of healthcare providers who work with a defined group of patients. PARTICIPANTS: Across the cases, 48 individuals participated, including SEM and other enhanced skill family physicians, generalist family physicians, residents, specialists, and administrative staff. MAIN OUTCOME MEASURES: Qualitative descriptions of the impacts of the SEM certificate on comprehensive care provision in Canada. RESULTS: SEM certificate holders experience enhanced well-being and professional satisfaction while also benefitting comprehensive care in communities in numerous ways. That SEM certificate holders may prioritize professional interests over community healthcare needs was identified as a potential drawback. Athletes and physically active individuals have specific healthcare needs, and may constitute a significant critical mass to be considered a community unto themselves. CONCLUSIONS: The SEM certificates impact healthcare positively when holders work in collaborative models that are well aligned with local community needs. Expanding the awareness of the scope of SEM and advocacy for adequate remuneration for these services have the potential to enhance SEM contributions to comprehensive family medicine in Canada.

Identifying aroma-active compounds in coffee-flavored dairy beverages.

Coffee aroma is a complex mixture of volatile compounds. This study characterized the important aroma-active compounds associated with consumer liking in formulated coffee-flavored dairy beverages. Nine coffee-flavored dairy beverages were formulated: low fat-low coffee; medium fat-low coffee; high fat-low coffee; low fat-medium coffee; medium fat-medium coffee; high fat-medium coffee; low fat-high coffee; medium fat-high coffee; and high fat-high coffee. Regular coffee consumers, (n = 231) used a nine-point hedonic scale to rate acceptance of aroma. Volatile compounds were extracted by head space-solid phase micro-extraction (HS-SPME) and analyzed by gas chromatography-mass spectrometry-olfactometry (GC-MS-O) using a modified frequency (MF) approach. Fifty-two aroma-active compounds were detected. Thirty-one aroma-active compounds were considered important compounds with MF-value ≥ 50%. The total number of aroma-active compounds and their intensity were affected because of fat and coffee concentration. Partial least squares regression (PLSR) was performed to determine the relationship between aroma-active compounds and liking. PLSR analysis identified three groups of compounds regarding liking. Twenty-five compounds were associated with positive liking, for example, 2-(methylsulfanylmethyl) furan (coffee like). Sixteen compounds were negatively associated with liking, for example, 2-methoxyphenol (bacon, medicine like). Eleven detected compounds had no association with liking, for example, butane-2,3-dione (butter, fruit like). Practical Application: The result of this study may be applied to formulate coffee-flavored dairy beverages to maximize consumer acceptance and aroma-liking. This study suggested too low coffee concentration is not desirable. Too much fat affects aroma release and/or alters the characteristic coffee flavor which negatively affects consumer acceptance.

Using Adaptive Sensors for Optimised Target Coverage in Wireless Sensor Networks.

Innovation in wireless communications and microtechnology has progressed day by day, and this has resulted in the creation of wireless sensor networks. This technology is utilised in a variety of settings, including battlefield surveillance, home security, and healthcare monitoring, among others. However, since tiny batteries with very little power are used, this technology has power and target monitoring issues. With the development of various architectures and algorithms, considerable research has been done to address these problems. The adaptive learning automata algorithm (ALAA) is a scheduling machine learning method that is utilised in this study. It offers a time-saving scheduling method. As a result, each sensor node in the network has been outfitted with learning automata, allowing them to choose their appropriate state at any given moment. The sensor is in one of two states: active or sleep. Several experiments were conducted to get the findings of the suggested method. Different parameters are utilised in this experiment to verify the consistency of the method for scheduling the sensor node so that it can cover all of the targets while using less power. The experimental findings indicate that the proposed method is an effective approach to schedule sensor nodes to monitor all targets while using less electricity. Finally, we have benchmarked our technique against the LADSC scheduling algorithm. All of the experimental data collected thus far demonstrate that the suggested method has justified the problem description and achieved the project's aim. Thus, while constructing an actual sensor network, our suggested algorithm may be utilised as a useful technique for scheduling sensor nodes.

Automatic Target Detection from Satellite Imagery Using Machine Learning.

Object detection is a vital step in satellite imagery-based computer vision applications such as precision agriculture, urban planning and defense applications. In satellite imagery, object detection is a very complicated task due to various reasons including low pixel resolution of objects and detection of small objects in the large scale (a single satellite image taken by Digital Globe comprises over 240 million pixels) satellite images. Object detection in satellite images has many challenges such as class variations, multiple objects pose, high variance in object size, illumination and a dense background. This study aims to compare the performance of existing deep learning algorithms for object detection in satellite imagery. We created the dataset of satellite imagery to perform object detection using convolutional neural network-based frameworks such as faster RCNN (faster region-based convolutional neural network), YOLO (you only look once), SSD (single-shot detector) and SIMRDWN (satellite imagery multiscale rapid detection with windowed networks). In addition to that, we also performed an analysis of these approaches in terms of accuracy and speed using the developed dataset of satellite imagery. The results showed that SIMRDWN has an accuracy of 97% on high-resolution images, while Faster RCNN has an accuracy of 95.31% on the standard resolution (1000 × 600). YOLOv3 has an accuracy of 94.20% on standard resolution (416 × 416) while on the other hand SSD has an accuracy of 84.61% on standard resolution (300 × 300). When it comes to speed and efficiency, YOLO is the obvious leader. In real-time surveillance, SIMRDWN fails. When YOLO takes 170 to 190 milliseconds to perform a task, SIMRDWN takes 5 to 103 milliseconds.