Utilization Of New Technologies Research Articles

Simultaneous Cu(II)-EDTA decomplexation and Cu(II) recovery using integrated contact-electro-catalysis and capacitive deionization from electroplating wastewater

The complex of heavy metals and organic acids leads to high difficulty in heavy metals separation by traditional technologies. Meanwhile, alkaline precipitation commonly used in industry causes the great consumption of resources and extra pollution. Herein, the effective decomplexation of Cu(Ⅱ)-EDTA and synchronous recycling of Cu2+ were realized by contact-electro-catalysis (CEC) coupled with capacitive deionization (CDI) innovatively. In particular, fluorinated ethylene propylene (FEP) as dielectric powders could generate reactive oxygen species under ultrasonic stimulation, realizing continuous deaminization and decarboxylation of Cu(Ⅱ)-EDTA and accelerating the totally breakage of Cu-O and Cu-N bonds. Additionally, the degradation pathway and intermediates evolution of Cu(Ⅱ)-EDTA were investigated using various characterization methods. It was confirmed that decarboxylation predominantly governed the degradation process of Cu(Ⅱ)-EDTA in CEC. During the course of treatment, the degradation ratio of Cu(Ⅱ)-EDTA reached 86.4 % within 150 min. Impressively, this strategy had satisfactory applicability to other metal combinations and excellent cycle stability. Subsequently, the released Cu ions were captured by CuSe cathode electrode through CDI. This research elucidated the degradation mechanism of persistent organic pollutant during CEC, and provided a novel approach for efficiently treating industrial wastewater containing metal complexes and advancing the exploitation and utilization of new technologies for metal recovery.

The Shadow of the Future: A Framework for Reform in Higher Education

The vast majority of professions practiced a century ago no longer exist, having been supplanted by robotics and other technological advancements. The Global Technology Network posits that the acceleration of technological unemployment is likely to emerge as one of the most challenging societal issues of the twenty-first century. While 'creative destruction', wherein obsolete job roles are replaced by new ones, will play a significant role, our latest technologies possess the potential to eliminate more jobs than they generate. Given the geometric progression of technological advancements, robotics, artificial intelligence, 3D printing, and other disruptive innovations are poised to significantly impact conventional professions in the labor market imminently. Billions of individuals worldwide are currently employed in industries likely to be affected, and billions more entering the workforce will require employment. Higher Education (HE) is confronted with dual challenges in this process: on one hand, it needs to align its entire knowledge production chain with these dynamic requirements to ensure its outputs remain relevant; on the other hand, it must undergo self-transformation to maintain its significance in the production of both technical and non-technical knowledge. This research endeavors to pinpoint Albania's position within these global trends and explores how HE in Albania can adapt without undergoing a catastrophic shock. We advocate for a fundamental overhaul of the higher education system, focusing on transforming the relationship between the state and higher education institutions. Starting from the premise that the socialist experiment with the university system has failed, we propose the outline of a potential reform that reimagines the role of stakeholders. The efficient utilization of new technologies could facilitate this transformation. Received: 25 December 2023 / Accepted: 25 February 2024 / Published: 23 April 2024

Optimizing an efficient urban tree strategy to improve microclimate conditions while considering water scarcity: a case study of Cairo

This study aims to develop an efficient urban tree strategy (UTS) to enhance the microclimate conditions of cities that suffer from heat stress and strong solar radiation, such as the metropolitan area of Greater Cairo. Cairo recently lost its limited greenery to enhance traffic. The proposed UTS aims to achieve a balance between enhancing microclimate conditions and considering the city’s water scarcity. It seeks to consider all strategic factors suitable for local conditions, including the selection of tree species (Step 1), the utilization of new technologies for irrigation (Step 2), and the optimization of the usage of an efficient number of trees (Step 3). When applying the strategy’s recommendations to a study area within Cairo’s downtown center and when testing different tree coverage percentages within urban canyons of various aspect ratios and orientations using ENVI-met, the microclimate conditions are significantly enhanced in certain streets during summertime compared to wintertime. Applying the UTS not only enhances thermal comfort but also helps to create a better comfort zone during certain hours. In one street, for example, there are average physiological equivalent temperature (PET) reductions of − 5.18° and − 6.36° at 16:00 and 17:00, respectively, which also changes the thermal comfort zone from extreme heat stress to very heat stress. The results show a strong positive correlation between thermal comfort enhancement and a reduction in the total mean radiant temperature (TMRT), verifying that shading plays a primary role in enhancing the microclimate conditions of urban canyons. Applying the UTS to the study area significantly enhances the microclimate conditions. Furthermore, through the implementation of irrigation technologies that are part of the UTS, water demand is reduced to only 15% when trees with larger canopies are used. Additionally, when the tree coverage percentage reaches 35 to 50% in some streets, it results in a significant enhancement in the PET.

Risk prevention and insurance. Reaching or trespassing the insurance boundaries?

Insurance presents a well-recognized preventive value. However, in recent times when it comes to the preventive function of insurance, it is about much more and this can be heard in voices of increasing numbers of experts and insurers. Three fundamental motivators prompted the pursuit of this study: (1) dynamic shifts in the risk landscape, (2) emerging technologies facilitating risk prevention, and (3) a perceived regulatory gap in addressing societal needs and technological potentials. Legal considerations related to the utilization of new technologies in insurance have been extensively discussed, albeit selectively. These discussions have focused on issues such as the policyholder’s risk declaration, the potential use of sensitive data for risk assessment, and the automated distribution process (robo-advice). No comprehensive legal analysis of the preventive function of insurance in this context is available. There is a noticeable research and publication gap that should be filled by holistic considerations on risk prevention in insurance, both on the level of private law (insurance contract, duties of the insurance distributors, as well as public law, concerning the supervision over applying the risk prevention measures by the insurance carriers. Finding a new approach that could address the legal challenges is, according to the author, of great importance for the development of insurance as a protection tool for the most imminent social risks. The objectives included in the paper include showing the impact of new technologies on risk prevention, as well as analysis of what the role of the insurer in risk prevention may and should be from the legal perspective, including the potential change of roles in performing the insurance contract. The objectives of the paper involve several aspects, such as whether prevention has the potential to become a distinguished (re-) insurance service, as well as what the boundaries of the insurance contract and insurance business in terms of its compensatory and preventive function are.

Nurses' Views on Caring for Lonely Patients During the Pandemic: A Qualitative Study.

The implementation of safety measures in hospitals due to the COVID-19 pandemic, including family visitation restrictions, forced the family to be absent during the patient's hospitalization. Nurses were confronted with new roles and responsibilities, as caring for lonely patients was a new phenomenon that emerged during the pandemic. The purpose of this study was to explore the nurses' views on caring for lonely patients during the COVID-19 pandemic. A qualitative research method based on an inductive content analysis approach was used. Data collection was carried out using semi-structured interviews. The sample consisted of 11 nurses who worked in COVID-19 wards and units. Content analysis was used to analyze the interview data. The analysis of the data revealed three main themes: 1) caring for the patient and the family; 2) extending conventional care; and 3) developing supportive mechanisms for better care. Caring for lonely patients brought about changes in patients's management and care and significantly affected communication patterns as well as nurses' roles and responsibilities. Providing care beyond limits, supporting care through the utilization of new technologies, and transforming organization and care were mentioned as areas of challenge for nursing practice. Conclusions: Maintaining communication and supporting the family's involvement in patient care are considered to be equal to healing for the lonely patient. Reshaping working conditions and caring practices to meet the needs of the nurses, the patients, and their families during health crises may contribute positively to the provision of holistic care for patients and their families.

New technological developments in medical education

Introduction: Medical education is a rapidly evolving field, necessitating adaptation to shifts in student demographics and societal needs. Balancing the demand for more healthcare providers must be accompanied by a focus on maintaining the quality of education. As certain conventional teaching methods lose favour, there is a continuous influx of new technologies that can be harnessed for the education of future doctors.
 Purpose of the study: The objective of this study was to gather and analyse literature on the utilization of new technologies in medical education and their influence on students, educators, and the overall quality of medical instruction.
 Material and methods: A review of the literature available on PubMed and a grey literature search was performed. We used such keywords like: “medical education”, “physician training”, “medical students”, “technology”, “elearning”, “new learning methods”. We also applied Bolean logical operators such as “AND”, “OR”. 
 Results: Examining the gathered publications leads to the conclusion that a variety of new technologies are being employed in medical education, such as e-learning, telehealth, and virtual or augmented reality. While some function as alternatives to existing methods, others introduce entirely novel approaches. In general, these new technologies positively impact education by enhancing outcomes, increasing accessibility to education, and reducing the costs associated with the teaching process.
 Conclusions: The integration of emerging technologies has become essential in the preparation of future medical professionals. Despite the overall positive impact, there are apprehensions regarding potential long-term consequences for healthcare delivery. Subsequent studies are crucial to assess lasting effects, delving into how the integration of technology may shape the skills of healthcare professionals over time.

Comprehensive assessment and treatment strategies for dysphagia in the elderly population: Current status and prospects.

As the population ages, the prevalence of dysphagia among older adults is a growing concern. Age-related declines in physiological function, coupled with neurological disorders and structural changes in the pharynx associated with aging, can result in weakened tongue propulsion, a prolonged reaction time of the submental muscles, delayed closure of the laryngeal vestibule, and delayed opening of the upper esophageal sphincter (UES), increasing the risk of dysphagia. Dysphagia impacts the physical health of the elderly, leading to serious complications such as dehydration, aspiration pneumonia, malnutrition, and even life-threatening conditions, and it also detrimentally affects their psychological and social well-being. There is a significant correlation between frailty, sarcopenia, and dysphagia in the elderly population. Therefore, older adults should be screened for dysphagia to identify both frailty and sarcopenia. A reasonable diagnostic approach for dysphagia involves screening, clinical assessment, and instrumental diagnosis. In terms of treatment, multidisciplinary collaboration, rehabilitation training, and the utilization of new technologies are essential. Future research will continue to concentrate on these areas to enhance the diagnosis and treatment of dysphagia, with the ultimate aim of enhancing the quality of life of the elderly population.

Rapid Determination of Wine Grape Maturity Level from pH, Titratable Acidity, and Sugar Content Using Non-Destructive In Situ Infrared Spectroscopy and Multi-Head Attention Convolutional Neural Networks

In the pursuit of enhancing the wine production process through the utilization of new technologies in viticulture, this study presents a novel approach for the rapid assessment of wine grape maturity levels using non-destructive, in situ infrared spectroscopy and artificial intelligence techniques. Building upon our previous work focused on estimating sugar content (∘Brix) from the visible and near-infrared (VNIR) and short-wave infrared (SWIR) regions, this research expands its scope to encompass pH and titratable acidity, critical parameters determining the grape maturity degree, and in turn, wine quality, offering a more representative estimation pathway. Data were collected from four grape varieties—Chardonnay, Malagouzia, Sauvignon Blanc, and Syrah—during the 2023 harvest and pre-harvest phenological stages in the vineyards of Ktima Gerovassiliou, northern Greece. A comprehensive spectral library was developed, covering the VNIR–SWIR spectrum (350–2500 nm), with measurements performed in situ. Ground truth data for pH, titratable acidity, and sugar content were obtained using conventional laboratory methods: total soluble solids (TSS) (∘Brix) by refractometry, titratable acidity by titration (expressed as mg tartaric acid per liter of must) and pH by a pH meter, analyzed at different maturation stages in the must samples. The maturity indicators were predicted from the point hyperspectral data by employing machine learning algorithms, including Partial Least Squares regression (PLS), Random Forest regression (RF), Support Vector Regression (SVR), and Convolutional Neural Networks (CNN), in conjunction with various pre-processing techniques. Multi-output models were also considered to simultaneously predict all three indicators to exploit their intercorrelations. A novel multi-input–multi-output CNN model was also proposed, incorporating a multi-head attention mechanism and enabling the identification of the spectral regions it focuses on, and thus having a higher interpretability degree. Our results indicate high accuracy in the estimation of sugar content, pH, and titratable acidity, with the best models yielding mean R2 values of 0.84, 0.76, and 0.79, respectively, across all properties. The multi-output models did not improve the prediction results compared to the best single-output models, and the proposed CNN model was on par with the next best model. The interpretability analysis highlighted that the CNN model focused on spectral regions associated with the presence of sugars (i.e., glucose and fructose) and of the carboxylic acid group. This study underscores the potential of portable spectrometry for real-time, non-destructive assessments of wine grape maturity, thereby providing valuable tools for informed decision making in the wine production industry. By integrating pH and titratable acidity into the analysis, our approach offers a holistic view of grape quality, facilitating more comprehensive and efficient viticultural practices.

The Challenges of Pain Assessment in Geriatric Patients With Dementia: A Review.

Pain in dementia patients is common, poorly measured, and undertreated. It is important to discuss the challenges in the pain assessment and management to find a possible solution for adequate pain management. The aim of this article is to discuss the challenges in the assessment of pain in geriatric patients with dementia. An extensive online database search was conducted via multiple websites using the following keywords: "dementia," "pain assessments," "pain assessment with dementia," "causes of pain with dementia," "pain assessments using recent technology," "geriatric," and "old age" to identify the relevant articles. Our inclusion criteria were articles that focused on pain in geriatric patients diagnosed with dementia, in English, published between January 2018 and January 2023, and available as free full text and those which were clinical trials, observational studies, review articles, systemic reviews, meta-analysis, or case series. The exclusion criteria were articles that did not have pain in geriatric patients diagnosed with dementia as their primary focus, involving geriatric or non-geriatric patients with major psychological distress, not in the English language, not published between January 2018 and January 2023, and not available as free full-text and those which were case reports and editorial articles. After manually excluding the articles that did not meet our inclusion criteria, we ended up with 38 articles. In conclusion, any instruments have been made for the pain assessment in patients with dementia. The two most common tools used to assess pain in this vulnerable population are the Pain Assessment in Advanced Dementia (PAINAD) and Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC) scales. The utilization of new technology may offer promising solutions for the pain assessment in patients with dementia.

Incorporation of Biotechnologies into Gene Banking Strategies to Facilitate Rapid Reconstitution of Populations.

National animal gene banks that are responsible for conserving livestock, poultry, and aquatic genetic resources need to be capable of utilizing a broad array of cryotechnologies coupled with assisted reproductive technologies to reconstitute either specific animals or populations/breeds as needed. This capability is predicated upon having sufficient genetic diversity (usually encapsulated by number of animals in the collection), units of germplasm or tissues, and the ability to reconstitute animals. While the Food and Agriculture Organization of the United Nations (FAO 2012, 2023) developed a set of guidelines for gene banks on these matters, those guidelines do not consider applications and utilization of newer technologies (e.g., primordial germ cells, cloning from somatic cells, embryo transfer, IVF, sex-sorted semen), which can radically change how gene banks collect, store, and utilize genetic resources. This paper reviews the current status of using newer technologies, explores how gene banks might make such technologies part of their routine operations, and illustrates how combining newer assisted reproductive technologies with older approaches enables populations to be reconstituted more efficiently.

Practical Considerations for the Implementation and Monitoring of Risk Minimisation Measures for High-Risk Teratogenic Medicines.

There is considerable societal interest in making medicines more affordable. A critical factor often inadequately considered early in the process of adding drugs to a company's product portfolio is that some products may require additional monitoring and complex, demanding and expensive additional risk minimisation measures (aRMMs). These aRMMs may have a sizeable impact on a company's commitment to that medicinal product throughout the product's entire life cycle. The teratogenic phthalimides were selected as an example of medicines that are recently being genericised and require a substantial commitment in terms of additional monitoring and aRMMs, most notably in the form of pregnancy prevention programmes (PPPs) with controlled distribution systems (CDSs). Implementing PPPs with CDSs is complex and demanding and encompasses all routine activities, aRMMs, local/regional Health Authority (HA) requirements, and commercialisation strategies. Considerations have been summarised that can support decision-making during due diligence processes, implementation and monitoring. Proactive, effective pharmacovigilance requires innovative, sustainable and flexible solutions to maintain high standards across the board. In particular, generic marketing authorisation holders operate with limited resources and may benefit appreciably from the following proposed suggestions and solutions such as early planning and preparation, knowledge-sharing, utilisation of new technologies and implementation of measures beyond HA-mandated requirements.

Internet of Things Based Horizontal Axis Tracking Solar Panel Performance Evaluation

Renewable energy is undergoing significant advancements through the utilization of new technologies. Among these technologies, fixed solar panels serve as a fundamental type of solar photovoltaic energy generator. Monitoring and optimizing the performance of these panels is achieved through the implementation of controller algorithms. However, there is a growing emphasis on axis tracking systems for solar panels, as that has the feasible to extract more power compared to fixed panels. In this context, the integration of the Internet of Things (IoT), big data analytics, deep learning, and cloud computing presents a contemporary solution for addressing various challenges associated with monitoring renewable solar energy systems. By employing sensors and actuators grouped within an IoT framework, real-time data can be extracted and stored in a cloud server, allowing remote access from anywhere. Furthermore, the use of meta-heuristic optimization algorithms, such as the Whale Optimization Algorithm, has become commonplace in solving engineering issues. In this proposed system, the performance of horizontal axis trackers is analyzed and compared with fixed panels using the WOA-based axis tracking analysis. Through the application of a control algorithm, optimal values can be obtained under typical weather conditions. The system’s simulation and performance are thoroughly assessed and evaluated.

Design and redesign of a bottom trawl survey in Chesapeake Bay, USA

Fisheries-independent surveys that reliably sample a broad size range of exploited and ecologically important species provide valuable data in support of fisheries management and ecosystem science. The operational consistency of surveys over time and space is fundamental to the interpretation of data in the contexts of population dynamics processes, community interactions, policy impacts, and environmental forcing. However, the need to maintain historic sampling protocols over extended time periods limits the utilization of new technologies that could lead to improved data collection. Survey vessel replacements also become inevitable as the maturity of sampling programs becomes multidecadal. This case study describes the motivational origin, initial design, and redesign of a bottom trawl survey operating in Chesapeake Bay, the largest estuary in the United States. Regional aspirations to consider ecosystem principles in fisheries management aided initial development of the survey, and the need to collect specific data types to support that endeavor impacted several early design elements. Following the beginning years of full-scale survey operations, a consistently evolving awareness of potential areas of improvement for the survey grew from formal efforts to engage with scientific and industry partners on trawl gear design, leverage the program for additional survey opportunities, utilize gear testing technology, and analyze extant data. When the delivery of a new, state-of-the-art research vessel forced the transfer of survey operations to a new platform, all potential changes were incorporated simultaneously. A subsequent paired-tow experiment was conducted to build a calibration database that successfully provided estimates of relative selectivity for routinely sampled taxa. This experience yielded several lessons learned that are intended to aid investigators faced with adopting structural changes to fisheries-independent surveys in the future.

Prospect of Direct Dimethyl Ether Production from CO2: Reactor Design Development

The increasing emissions of carbon dioxide (CO2) and volatile hydrocarbons via burning of fossil fuels result in a significant amount of global warming and air pollution. With the concern over the impact of fossil fuel to the environment, the interest in alternative fuel production from the CO2 generated through utilization of new technologies has risen rapidly. Several clean alternative fuels, including dimethyl ether (DME) have been investigated for a more sustainable and greener environment. DME has a high cetane number but produces much lower NOx emission upon combustion. DME is typically synthesized using syngas based on conventional indirect DME route, where the process begins with conversion of syngas into methanol and subsequently dehydrated to DME in separate units. Recently, a direct single-step route to produce DME through dehydrogenation of CO2 and dehydration of methanol by utilising a novel bifunctional catalyst has been investigated. In direct DME, the dehydrogenation and dehydration occur simultaneously in a single reactor, which eliminate the need for a methanol production plant. However, the use of conventional fixed-bed reactor (FBR) for the direct DME synthesis causes many challenges including catalyst deactivation, where water appears in the reaction area, limiting the conversion of CO2 reactants into DME and consequently, the DME yield. It is also essential to manage the exothermic heat generated from the catalyst for better DME yield. In order to overcome these hurdles, several types of reactors have been proposed such as fluidized bed reactor, slurry reactor, microreactor and catalytic membrane reactor. In this paper, different types of reactors are first discussed and its applications related to the direct DME production from CO2 are highlighted. Finally, the challenges and difficulties of reactor development are addressed and future direction is outlined.

Human employees versus robotic employees: Customers and hotel managers’ perceived experience at unmanned smart hotels

Hotel managers and researchers are increasingly interested in artificial intelligence (AI) and robots, which are vital to the future of the hospitality industry. However, adopting robotic services is challenging due to the current state of the art and insufficient understanding of the relationship between customer satisfaction and robotic services. Hotels are building a competitive advantage through high technology permeating various service environments. This study examined customer perceptions and satisfaction with smart hotels during COVID-19 based on online reviews by building a list of smart hotel properties that identifies well-performing and poorly performing service quality. Results highlight the advantages of smart hotels in the tourism environment and provide helpful guidance for hoteliers to apply high technology in the service environment. This study examines and demonstrates that the utility of new technologies in a smart hotel at modern times to deal with the challenges of COVID-19, and assures precision and speed in service delivery to improve sustained competition and guest experience.

A Review of Rock Slope Stability Assessment Practice in Malaysia

Rock slope stability assessment in Malaysia has become increasingly important as new developments encroach hillsides around major cities. This article reviews historical case studies to present a general picture of rock slope assessment practice in Malaysia, especially on methods and output of the case studies. Common methods include use of locally developed rating systems, Rock Mass Rating (RMR) and its derivatives, kinematic analysis, and numerical analysis. Application of these methods must be suitable with site conditions, while its advantages and disadvantages must be recognized by the assessor. Emergence of new technologies greatly improves the speed and quality of data acquisition provided. A total of 39 case studies on different lithologies were examined, in which progress were notable from kinematic analysis-based assessments to incorporation of rating systems and numerical analysis. This article recommends several improvements for rock slope assessment practice. These include an establishment of a local good practice guide in the assessment, incorporation of numerical analysis into standard practice, improving utilization of new technologies, more attention to the influence of weathering, and consideration of seismic influence in seismically active regions. Utilization of numerical methods and other contemporary methods reflects increasing understanding of rock mechanics which is vital to rock slope stability assessment among local practitioners. Improved rock slope assessment allows for a more accurate stability determination and decisive mitigation measure recommendations, which is to be done by competent engineering geologists, in line with Geologist Act 2008.

Analysis of Technology Involvement in Islamic Religious Education Learning

The utilization of new technologies in Islamic educational practices is an undeniable necessity at this time. This article analyzes how Islamic religious education utilizes technology in the teaching and learning process, as well as the difficulties related with implementing this technology. This study employed a qualitative research approach in the form of a literature review to collect its data. According to the research findings, technology serves multiple functions and contributes to a variety of Islamic religious education components. This includes evaluation tools, transmission media, and design and planning forums for learning. Other findings explain some of the obstacles teachers face when utilizing technology, such as the need for more technological skills and infrastructure. On the basis of this study's findings, recommendations have been developed to enhance teachers' and students' understanding of how to maximize available technology by engaging in an intensive learning process.
 Keywords: engagement; Islamic education; learning technologies

Banks 4.0 in the Context of sustainable development: A literature review and research framework

The digitalization of banking services requires a focus on sustainable development as well as the utilization of new technologies. Understanding and predicting evolving customer needs and expectations is a vital objective for banks. This approach enables achieving and sustaining optimal customer satisfaction, leading to the establishment of customer loyalty It is crucial to examine how Industry 4.0 affects the transformation of the banking industry. It is necessary to prioritize finding a balance between competition, innovation, security, and customer satisfaction to ensure sustainable development. This paper aims to explore the implementation of Industry 4.0 technologies in the banking system and increase awareness among researchers and bank managers about these new technologies and the concept of sustainability. Through an analysis of relevant literature, we hope to provide valuable insights. In this regard, it presents a framework studying the critical components for achieving banking 4.0

Utilizing digital storytelling as a tool for teaching literature through constructivist learning theory.

Utilization of new technologies (ICT) and digital media has been a priority in recent years in the design and the implementation of educational programs around the world. The new educational reality, imposed by the pandemic, relies heavily on the replacement of in-person learning with distance learning, which is based on the use of digital tools and new technologies. The fact that distance learning has been massively and rapidly imposed due to the circumstances resulting from the pandemic and has been transformed from a supplementary to the main means of the educational procedure, has also highlighted the need for its tools to be linked to learning theories and to be extended to non-formal forms of education. Digital storytelling, in particular, that during the last years has been used as a means to all levels of formal and non-formal education, can be proved equally useful and productive in distance learning as well. This article presents a lesson plan for the literature course created in a secondary school in Greece. During the teaching, it was explored whether digital storytelling can provide a quality educational tool in which you can find a field for modern constructive–collaborative learning theories, in both formal and non-formal forms of education.

The Smart in Smart Cities: A Framework for Image Classification Using Deep Learning.

The need for a smart city is more pressing today due to the recent pandemic, lockouts, climate changes, population growth, and limitations on availability/access to natural resources. However, these challenges can be better faced with the utilization of new technologies. The zoning design of smart cities can mitigate these challenges. It identifies the main components of a new smart city and then proposes a general framework for designing a smart city that tackles these elements. Then, we propose a technology-driven model to support this framework. A mapping between the proposed general framework and the proposed technology model is then introduced. To highlight the importance and usefulness of the proposed framework, we designed and implemented a smart image handling system targeted at non-technical personnel. The high cost, security, and inconvenience issues may limit the cities’ abilities to adopt such solutions. Therefore, this work also proposes to design and implement a generalized image processing model using deep learning. The proposed model accepts images from users, then performs self-tuning operations to select the best deep network, and finally produces the required insights without any human intervention. This helps in automating the decision-making process without the need for a specialized data scientist.