Data Management Capabilities Research Articles

Architectural views for social robots in public spaces: business, system, and security strategies

This study delineates a suite of architectural views and a security perspective tailored to guide the deployment and integration of Social Robots in Public Spaces (SRPS). It commences with a business context view that utilizes the customer-producer-supplier model, underscoring the value of SRPS to various stakeholders and illustrating how robots can enhance user experiences and drive economic benefits. The system context view details the intricate interactions among the social robot, stakeholders, public spaces, and external systems, highlighting essential considerations for successful deployment, from technical configurations to stakeholder engagement. The functional view elaborates on the operational dynamics of the robot within its environment, focusing on user interaction and data management capabilities. Additionally, the security perspective delves into security considerations vital for safeguarding the SRPS across various domains, including identity and access management, application and network security, and data privacy. The paper also contextualizes these views through a city ferry use case, demonstrating their practical application and reinforcing the importance of multifaceted planning and analysis in real-world settings. This approach provides a strategic framework views for developing SRPS that are viable, efficient, and secure, fostering successful adoption in diverse public environments.

Synergizing Ai and ERP for Predictive Supply Chain Management and Quality Assurance in Healthcare

This article explores the transformative potential of integrating Artificial Intelligence (AI) with Enterprise Resource Planning (ERP) systems in healthcare, focusing on applications in predictive supply chain management and quality assurance. The healthcare industry faces increasing pressure to improve efficiency while maintaining high-quality care, and AI-ERP integration offers a compelling solution. By combining ERP's comprehensive data management capabilities with AI's predictive and analytical power, healthcare organizations can enhance operational efficiency, improve decision-making, and ultimately deliver better patient outcomes. The article examines current implementations, case studies, and future projections to provide a comprehensive overview of how this technological synergy can help healthcare providers navigate the complex challenges of modern healthcare delivery, from optimizing inventory levels to ensuring regulatory compliance and proactive risk management.

AI in Healthcare: Bridging the Gap between Research and Clinical Implementation

Artificial intelligence (AI) has the potential to revolutionize healthcare by enhancing diagnostic accuracy, reducing administrative burdens, and providing personalized treatment. However, the slow adoption of AI in healthcare is due to obstacles associated with ethical considerations, data management, regulations, and technological capabilities. The results of our study highlight specific challenges related to ethics, technology, regulatory, social, economic, and workforce barriers that affect the implementation of AI in healthcare. We aim to improve current knowledge by providing a more comprehensive understanding, by bridging the gap, and addressing the barriers to implement AI in the healthcare sector.

The Growing Trend of Cloud-Based Data Integration and Warehousing

This article examines the growing trend of cloud-based data integration and warehousing solutions in response to the exponential growth of data generation and the need for scalable, flexible analytics capabilities. It explores the key drivers behind cloud adoption, including data volume increases, demand for real-time insights, cost efficiencies, and advanced analytics requirements. The benefits of cloud solutions are discussed, such as scalability, cost-effectiveness, agility, and enhanced analytical capabilities. The article also addresses challenges like data security, vendor lock-in, and performance issues, providing best practices for successful implementation. Emerging trends in automated ETL processes, machine learning integration, and multi-cloud approaches are highlighted, showcasing the evolving landscape of cloud-based data management. Through analysis of market projections, case studies, and industry statistics, this comprehensive overview equips organizations with the knowledge to leverage cloud technologies to transform their data management capabilities and gain competitive advantages in the digital age.

Optimizing data management in healthcare: Lessons from clinical trials and beyond

This study comprehensively explores the optimization of data management in healthcare by drawing on lessons learned from clinical trials and extending these insights to broader healthcare contexts. The study's purpose is to examine the challenges, strategies, and technological innovations that are essential for effective data management in modern healthcare systems. Utilizing a detailed literature review, the study identifies key methodologies from clinical trials that have successfully enhanced data integrity, accuracy, and security, such as the implementation of electronic data capture (EDC) systems and rigorous data governance frameworks. These methods are crucial in managing the increasing volume and complexity of healthcare data. The study's findings reveal that big data analytics and artificial intelligence (AI) are pivotal in transforming healthcare data management, enabling personalized and precise patient care. However, these technologies also introduce challenges related to data security, interoperability, and ethical considerations, particularly concerning patient privacy and the transparency of AI-driven decision-making processes. In conclusion, the study emphasizes the need for continuous innovation and improvement in healthcare data management practices. Recommendations include the integration of blockchain technology, cloud computing, and real-time data from wearable devices to address existing challenges and enhance data management capabilities. The study advocates for a balanced approach that prioritizes patient privacy, ethical governance, and regulatory compliance to ensure that technological advancements contribute positively to patient outcomes and healthcare efficiency.

DIGITALIZATION AS A MEANS OF OVERCOMING CHALLENGES AND THREATS OF CONSTRUCTION PARTICIPANTS IN A MULTIPROJECT ENVIRONMENT

This article examines the potential of digitalization as a strategic solution to address the challenges and threats faced by construction actors in a multi-project environment.Construction activities are inherently complex, often characterized by the simultaneous management of several projects, each with its own characteristics and challenges. In a multi-project environment, participants such as designers, developers, and contractors face significant obstacles, including resource allocation conflicts, communication barriers, inefficiencies, and increased risk of delays and cost overruns. The advent of digital technology offers a transformative approach to these challenges, enabling more efficient management and coordination across multiple projects. The main objective of this paper is to explore how digital tools and technologies can mitigate the specific challenges faced by different actors during the construction of multiple projects. Analyzing key issues such as scheduling conflicts, miscommunication, data management complexity and risk management difficulties, the article highlights critical areas where digitization can have a significant impact.One of the most urgent problems in a multi-project environment is the effective allocation and planning of resources. Traditional management approaches often fail to cope with overlapping schedules and competing priorities, resulting in delays and inefficiencies. Digital tools such as Building Information Modeling (BIM) and Project Management Information Systems (PMIS) offer integrated platforms that facilitate seamless coordination and real-time updates. These systems provide centralized data stores and sophisticated scheduling algorithms that improve decision-making and reduce the likelihood of conflicts.Communication barriers are another major problem in multi-project environments that can lead to misunderstandings, errors, and delays that negatively impact project timelines and outcomes. Digital communication platforms, including instant messaging, video conferencing, and collaboration software, enhance real-time communication and ensure alignment among all stakeholders. These platforms enable the rapid exchange of critical information and facilitate the collaborative environment necessary to manage multiple projects simultaneously.Ensuring that all stakeholders have access to accurate and up-to-date information is critical to effective decision-making. Digitization solves this problem by providing advanced data management and analytics capabilities. Big data analytics and artificial intelligence can analyze large data sets to predict potential problems and optimize resource allocation. These technologies help identify trends, predict project outcomes, and facilitate informed decision-making, ultimately increasing project efficiency and effectiveness.Risk management is particularly challenging in a multi-project environment due to increased complexity and interdependence. Digital risk management tools offer a framework for identifying, assessing and mitigating risks across projects. These tools provide scenario analysis, risk tracking and automatic alerts, enabling proactive risk management and reducing the likelihood of project failure.

An e-learning platform for clinical reasoning in cardiovascular diseases: a study reporting on learner and tutor satisfaction

BackgroundMedical students gain essential skills through hospital training and internships, which complement their theoretical education. However, virtual patient platforms have been shown to effectively promote clinical reasoning and enhance learning outcomes. This study evaluates a web-based platform designed for learning clinical reasoning in cardiovascular diseases, detailing its functionalities and user satisfaction.MethodsThe Virtual Patient platform presents medical students with clinically valid scenarios, encompassing stages such as patient description, anamnesis, objective examination, presumptive diagnosis, health investigations, treatment planning, complications, differential and final diagnoses, and prognosis. Scenarios are generated either automatically or manually by professors, based on labeled and annotated clinical data. The Virtual Patient contains two types of medical cases: simple scenarios describing patients with one pathology, and complex scenarios describing patients with several related pathologies. The platform was evaluated by a total of 210 users: 178 medical students, 7 professors, and 25 engineering students, using questionnaires adjusted for each evaluation round to assess satisfaction and gather feedback. The evaluation by medical students was performed in four rounds, each round corresponding to successive enhancements of the platform functionalities and addition of new cases, with a total number of 1,098 evaluation sessions.ResultsThe platform was evaluated at different implementation stages, involving simple and complex scenarios for various heart diseases. The majority of students found the platform very useful (82.58%), with significant appreciation for its features and functionalities, for example the dialogue module supporting natural language interactions in Romanian and English or the feed-back obtained during interaction. Professors highly valued the platform’s flexibility in scenario generation, real-time feedback provision, and data management capabilities. They appreciated the possibility to provide feedback and score student performance in real-time or after the session, though some professors suggested improving the explainability of the scores.ConclusionsThe Virtual Patient platform enables medical students to virtually replicate hospital interactions, diagnose patients, and plan treatments in clinically valid scenarios for cardiovascular diseases. User evaluations demonstrated high satisfaction and appreciation for the platform’s features. Future work will focus on expanding medical cases, enhancing the dialogue module, improving scenario generation for complex cases, and extending the synthetic data generation component to produce additional types of medical investigations.

Abstract P330: Next-Gen Hypertension Control: Integrating Clinical Pharmacists And Cutting-Edge EPIC Electronic Medical Record For Quality And Result Driven Approaches at Federally Qualified Health Centers

Hypertension management in Federally Qualified Health Centers (FQHCs) requires innovative and comprehensive strategies beyond traditional methods. This study explores a collaborative approach by integrating clinical pharmacists into the healthcare team and utilizing the EPIC Electronic Medical Record (EMR) system. The model addresses medical and non-medical health determinants, offering comprehensive treatment for underserved communities regardless of their ability to pay. We hypothesized that integrating clinical pharmacists would improve and sustain blood pressure control, resulting in more patients achieving their target health outcomes. As part of multidisciplinary teams, clinical pharmacists identify, track, and analyze patient data, manage medication therapies under collaborative practice agreements, and coordinate with other healthcare providers to ensure continuous care. By leveraging EPIC EMR’s data management and patient monitoring capabilities, clinical pharmacists use real-time data to tailor medication regimens, ensure timely interventions, and conduct follow-ups every 2 to 4 weeks via telemedicine or in-clinic visits until patients reach their goals. This approach enhances patient engagement and medication adherence, which is crucial for adequate blood pressure control and cost management. It also supports personalized care addressing medical needs, lifestyle, and socioeconomic factors affecting patient health. The study, initiated in January 2024, involves adult patients with hypertension at one of the largest FQHC in Houston, TX. Key performance indicators include the percentage of patients achieving target blood pressure levels, medication adherence rates, and the frequency of follow-up visits. Preliminary data from quarter 1, 2024, shows that out of 327 patients, 58% have had at least 2 consultations with a clinical pharmacist. Out of those patients, 46% reached blood pressure control below 140/90 mmHg, while 27% showed improvement toward their goal. This quality and result-driven approach elevates hypertension management standards, reduces health disparities, and enhances healthcare delivery within FQHCs. Clinical pharmacists have proven to be indispensable members of the healthcare team. This session aims to provide practical insights and strategies for healthcare professionals to implement similar models, paving the way for the future of hypertension care.

Exploring Data Persistence in Android using Room Database

This research paper explore the concept of data persistence in Android applications using Room database. In the dynamic landscape of mobile app development, ensuring efficient storage and retrieval of data is crucial for providing a seamless user experience. Room database, a powerful library provided by Android Jetpack, offers a robust solution for managing app's local database. The study delves into the key features and benefits of Room database, including its support for object-relational mapping (ORM) and simplified SQLite database interactions. By analyzing the working principles and implementation strategies of Room, this research aims to provide developers with insights into optimizing data persistence in Android applications. Additionally, the paper discusses practical examples and best practices for integrating Room database into Android projects, highlighting its role in enhancing data management capabilities and improving overall app performance. By examining the impact of Room database on data persistence in Android apps, this research contributes to the ongoing discourse on efficient storage solutions for mobile applications Keywords: Room, Android, Dao, Entity, SQLite, Recycler View, ViewHolder, Dependency, Adapter, Gradle

The differential impact of IT investments in the long term: a long-horizon event study

PurposeThis research investigates the differential impact of information technology (IT) investments based on their features, such as investment in data management capability, security improvement, IT outsourcing or new IT infrastructure. The Long-Horizon Event Study (LHES) is essential for providing a more appropriate measure of the value of IT investments because firms' strategic decisions often set long-horizon and large-scale organizational goals, and there is inherent uncertainty regarding future cash flows resulting from these investments. Therefore, the authors aim to analyze how announcements of IT investments affect the firm's abnormal stock returns over the long term and to compare the differential impact of different features of IT investment.Design/methodology/approachThe authors gathered IT investment announcements and stock data of listed firms in Korea between 2000 and 2018, and the monthly stock market returns over the 5 years after the announcements. To measure the differential impact of IT investments based on the investment features, the authors separate announcements data into five groups. A LHES is used to estimate the long-term effects of IT investment announcements.FindingsThe results indicate that announcements of IT investments had a long-term positive effect on firm performance. Additionally, the findings reveal differential effects of IT investments across industries and investment features. Notably, news of self-developed IT investments and IT investments in the manufacturing industry had significantly positive effects. However, contrary to common belief, announcements of investments in so-called essential IT areas such as data, security, or new IT infrastructure did not yield significant effects.Originality/valueAlthough the need for LHES has been emphasized in information systems research, few follow-up studies have been conducted since Barua and Mani (2018). This is primarily due to the challenges associated with collecting large-scale abnormal stock returns data over a long horizon. This research represents the first LHES to investigate the differential impact of IT investments based on their features. By doing so, this study can provide valuable insights for decision-makers within firms, helping them understand the time horizon of market outcomes of IT investments based on their features. Furthermore, this work extends the scope of LHES to comprehend the differential impacts of investment features. For instance, managers need to grasp that so-called essential IT investments, such as data management, security enhancements or new IT infrastructure, may not necessarily generate long-term market value.

College Management System using Python & Django

The College Management System (CMS) is an advanced web-based application designed to streamline administrative and academic processes within educational institutions. Developed using the Django framework for backend functionalities and HTML, CSS, and JavaScript for frontend presentation, the CMS offers a comprehensive solution for managing various tasks efficiently. Leveraging SQLite as the databadminisratiase management system ensures robust data management capabilities, scalability, and ease of maintenance. The CMS provides a wide array of features to automate routine tasks and enhance collaboration among students, faculty, and administrators. Student admission and enrollment management, course scheduling, curriculum planning, and faculty assignment are seamlessly handled by the system, reducing manual workload and minimizing errors. Integrated messaging systems and announcement boards facilitate communication, fostering a collaborative learning environment. The examination management module automates the entire examination process, including exam scheduling, creation of question papers, venue allocation, and result processing. Online exam registration and automated grading streamline the process, ensuring accuracy and transparency while reducing administrative burden. Attendance tracking is simplified with the CMS, allowing faculty to record and monitor student attendance easily. Integration with biometric systems or RFID technology enhances accuracy and eliminates manual attendance taking. Comprehensive attendance reports provide insights into student progress and compliance with attendance policies. Resource management is optimized through the CMS, which enables efficient allocation and utilization of classrooms, laboratories, library resources, and equipment. Administrators can manage inventory, track asset availability, and schedule resource bookings to prevent conflicts and ensure optimal utilization. Reporting and analytics features empower administrators with real-time insights into various aspects of college operations. Customizable dashboards provide information on enrollment statistics, academic performance, financial data, and more, enabling informed decision-making and continuous improvement. In conclusion, the College Management System developed with Django, HTML/CSS/JS, and SQLite revolutionizes educational institution management. By combining advanced technology with intuitive design, the CMS enhances efficiency, transparency, and collaboration, ultimately contributing to the success and growth of the institution.

Analysis of Risk Management Using E-Office Application with ISO 31000:2018 in National Public Procurement Agency (NPPA/LKPP)

The National Public Procurement Agency (NPPA/LKPP) has implemented the E-Office application to streamline work activities for both civil servant (ASN) and non-ASN employees, encompassing personnel data, attendance, correspondence, and other administrative functions. This research aims to identify and analyze the risks associated with the LKPP E-Office application. This study utilized a qualitative methodology, adhering to the ISO 31000:2018 risk management framework, to conduct in-depth interviews and observations within the LKPP setting. The aim was to gather comprehensive data to support stakeholders in making well-informed and precise policy decisions about the E-Office application. Through this research, 32 distinct risks were identified and categorized into high, moderate, and low levels based on their potential impact. This study developed specific mitigation strategies to address and minimize the effect of identified risks. By adopting these strategies, the research aims to enhance the reliability and security of the E-Office application. Improved risk management practices will lead to a more resilient and secure system. As a result, boosting administrative efficiency and data management capabilities within NPPA/LKPP. Furthermore, this research not only brings to light the critical areas that require immediate attention but also outlines a strategic roadmap for mitigating these risks. This approach ensures the sustainable and efficient operation of the E-Office application. The outcomes of this study are anticipated to offer substantial benefits to stakeholders, creating a more secure and efficient administrative environment.

LUNGBANK: a novel biorepository strategy tailored for comprehensive multiomics analysis and P-medicine applications in lung cancer.

LUNGBANK was established as part of Project LUNGMARK, pioneering a biorepository dedicated exclusively to lung cancer research. It employs cutting-edge technologies to streamline the handling of biospecimens, ensuring the acquisition of high-quality samples. This infrastructure is fortified with robust data management capabilities, enabling seamless integration of diverse datasets. LUNGBANK functions not merely as a repository but as a sophisticated platform crucial for advancing lung cancer research, poised to facilitate significant discoveries. LUNGBANK was meticulously designed to optimize every stage of biospecimen handling, from collection and storage to processing. Rigorous standard operating procedures and stringent quality control measures guarantee the integrity of collected biospecimens. Advanced data management protocols facilitate the efficient integration and analysis of various datasets, enhancing the depth and breadth of research possibilities in lung cancer. LUNGBANK has amassed a comprehensive collection of biospecimens essential for unraveling the intricate molecular mechanisms of lung cancer. The integration of state-of-the-art technologies ensures the acquisition of top-tier data, fostering breakthroughs in translational and histological research. Moreover, the establishment of patient-derived systems by LUNGBANK underscores its pivotal role in personalized medicine approaches. The establishment of LUNGBANK marks a significant milestone in addressing the critical challenges of lung cancer research. By providing researchers with high-quality biospecimens and advanced research tools, LUNGBANK not only supports Project LUNGMARK's objectives but also contributes extensively to the broader landscape of personalized medicine. It promises to enhance our understanding of lung cancer initiation, progression, and therapeutic interventions tailored to individual patient needs, thereby advancing the field towards more effective diagnostic and therapeutic strategies.

Comprehensive Review of Smart Cities using IOT in Coud

The rapid growth of urbanization necessitates smarter and more sustainable city management. The convergence of Internet of Things (IoT) devices and cloud computing offers a transformative solution for building Smart Cities. This review explores the integration of IoT and cloud technologies in creating intelligent urban infrastructure. It examines how data collected from a network of sensors and devices across the city can be leveraged to improve various aspects of urban life, including traffic management, energy efficiency, public safety, waste management, and parking. The paper discusses the key benefits of cloud computing for Smart City IoT applications, such as scalability, centralized data management, cost-effectiveness, security, and advanced analytics capabilities. Additionally, it explores the challenges associated with implementing Smart City IoT solutions, such as data privacy concerns, cybersecurity risks, and the need for interoperability between different devices and platforms. Finally, the review concludes by highlighting the potential of Smart City IoT powered by cloud computing to create a more efficient, sustainable, and livable future for our cities.

The applications of building information modeling in the life-cycle of green buildings: a comprehensive review

Previous research indicates that Building Information Modeling (BIM) serves as a digital platform for integrating pertinent data across all stages of construction, enhancing data management capabilities. This is notably crucial during initial investment planning and throughout project execution, facilitating efficient engineering information management, practice, quality assurance, and cost control concurrently. BIM contributes novel insights into green building development while posing significant challenges. The complexity of optimizing multiple performance indicators using BIM has hindered its widespread adoption in design practice, confining its application primarily to academic research. Therefore, this paper reviewed 168 previous studies from the past ten years, conducted an in-depth review and comparison, and provides suggestions for possible future research direction for BIM research. Specifically, the paper systematically reviews the application of BIM in design, construction, operation and maintenance, retrofit and demolition, and all the assessment phases of green buildings, and discusses the advantages of the BIM application in green buildings as well as an analysis of the current research gaps. This research enhances practitioners’ understanding of BIM and green buildings’ current trends and development status. It elucidates BIM's role in fostering green building development, guiding future industry professionals and researchers in effectively integrating BIM into sustainable construction practices.

Student Result Management System using PHP

Our educational institution maintains digital records of student data to ensure ease of access and management. However, these records are currently dispersed across various formats, posing challenges in maintenance, especially with the growing student population. This fragmentation often results in redundant data entry and inconsistencies, as students are required to repeatedly provide the same information. In response, we propose the development of a comprehensive web application designed to function as an integrated platform for aggregating and categorizing student data. This platform aims to consolidate all student-provided information into a centralized repository, which can then be categorized and selectively accessed by different user types according to their respective needs. Additionally, the web application will empower students to effortlessly update their information while facilitating efficient retrieval of selected student data by college staff. Moreover, it will streamline the online admission process by offering the option of online payment through a secure payment gateway. Furthermore, the application will include features for recording student marks in their respective courses, as well as tracking attendance. It will also inform students of new placement opportunities offered by the college and maintain records of faculty and departments. Additionally, it will log online transactions conducted by students during the admission process. The development of this application will utilize HTML, CSS, and JavaScript for the front-end, ensuring an intuitive and visually appealing user interface. On the backend, PHP and MySQL will be employed to provide robust data management and processing capabilities

Real-Time Clickstream Analytics with Apache

The purpose of this research work is to provide an overview of setting up an Apache-based real-time clickstream data lifecycle for user behaviour analysis and marketing strategy improvement. It uses tools like Apache Kafka, Apache Spark, Amazon S3, AWS Glue Data Catalog, Hive Metastore, and Tableau to meet the challenges of data collecting, purification, and storage. The design offers rapid data processing and analysis using Spark, high-throughput and fault-tolerant data import with Kafka, and scalable storage in Amazon S3. Data retrieval, querying, and transformation are made easier by AWS Glue Data Catalogue and Hive Metastore, while Tableau offers interactive visualisations. Data management capabilities are improved by optional interaction with a data warehouse and data lake. The scalable architecture accommodates increased data quantities and user traffic, and a mathematical model derives useful insights from clickstream data.

Student Result Management System using PHP

Our educational institution maintains digital records of student data to ensure ease of access and management. However, these records are currently dispersed across various formats, posing challenges in maintenance, especially with the growing student population. This fragmentation often results in redundant data entry and inconsistencies, as students are required to repeatedly provide the same information. In response, we propose the development of a comprehensive web application designed to function as an integrated platform for aggregating and categorizing student data. This platform aims to consolidate all student-provided information into a centralized repository, which can then be categorized and selectively accessed by different user types according to their respective needs. Additionally, the web application will empower students to effortlessly update their information while facilitating efficient retrieval of selected student data by college staff. Moreover, it will streamline the online admission process by offering the option of online payment through a secure payment gateway. Furthermore, the application will include features for recording student marks in their respective courses, as well as tracking attendance. It will also inform students of new placement opportunities offered by the college and maintain records of faculty and departments. Additionally, it will log online transactions conducted by students during the admission process. The development of this application will utilize HTML, CSS, and JavaScript for the front-end, ensuring an intuitive and visually appealing user interface. On the backend, PHP and MySQL will be employed to provide robust data management and processing capabilities

A Study on Automated Hospital Management System in Nigeria

This thesis underscores the critical importance of effective data management in the operational and survival aspects of contemporary hospitals. Acknowledging the imperative for continuous enhancements in this domain, the study recommends a proactive approach to explore and advance the existing hospital data management project by transitioning it to an online platform. This strategic move includes the implementation of robust security measures, particularly a secure access code system, to fortify the protection of sensitive information. The proposed transition aims not only to modernize the hospital's data management capabilities but also to establish a secure online infrastructure, guarding against unauthorized access and ensuring the integrity and confidentiality of critical healthcare data. The thesis concludes with a comprehensive overview of the development process for the computerized system. A detailed survey of the existing system laid the groundwork for the meticulous design of a database application focused on facilitating the search and retrieval of patient folders. The anticipated automated hospital management system is poised to significantly enhance the overall efficiency of healthcare services for both nurses and doctors, introducing notable improvements such as reduced time spent on locating patient folders, increased accuracy, and timely record preparation. Throughout the implementation phase, substantial efforts were dedicated to eliminating data redundancy and inconsistency, with a specific emphasis on enhancing the integrity of the stored data. The chosen software model, the waterfall model, provided a systematic and sequential approach to software development. Additionally, a structured design methodology was employed during the design stage to ensure clarity and efficiency. Recognizing the sensitivity of healthcare data, the thesis rigorously addresses security concerns by incorporating robust measures into the computerized system. These measures are designed to prevent unauthorized access, safeguarding the confidentiality and privacy of stored data. This multi-faceted approach to system development underscores the commitment to delivering a robust, efficient, and secure automated hospital management system aligned with the evolving needs of healthcare professionals, guaranteeing top-tier levels of data integrity and security.

WiSeCart: Sensor-based Smart-Cart with Self-Payment Mode to Improve Shopping Experience and Inventory Management

Superstores are often rippled with people from a variety of the pyramid structure from lower, middle and higher-levels of the pyramid. These malls often transform onto a busy-bee hub with people wishing to explore the merits of discounted product prices and special offers. This, however causes a surge in traffic coupled with the enticing promotions that then lead to endless queues at the various cash-sales point and check-out counters. This case often poses inherent challenges both for business owners and customers due to time constraint, product substitution and quantity tracking in such malls. The study proposes WiSeCart – a wireless sensor-based shopping cart with near feature compatibility feat. Result shows that the integration of a self-payment system via the NFC tech provisions the system with: (a) reduced queue time so that customers can finish their shopping quicker with fast-paced checkout process, (b) yields increase inventory management efficiency with reduced errors from customer data entry using NFC communication stickers, and (c) improved data management capability that allow for further study of customer behaviour for improved customer experience and service delivery, which will in turn equip business owner with better managerial decision support. Keywords: wireless sensor-networks, smart-carts, shopping trolley, customer experience, superstores Journal Reference Format: Brizimor, S.E., Okpor, M.D., Yoro, R.E., Emordi, F.U., Ifioko, A.M., Odiakaose, C.C., Ojugo, A.A., Ejeh, P.O., Abere, R.A., Ako, R.E., Geteloma, V.O., (2024): WiSeCart: Sensor-based Smart-Cart with Self-Payment Mode to Improve Shopping Experience and Inventory Management. Social Informatics, Business, Politics, Law, Environmental Sciences & Technology Journal. Vol. 10, No. 1. Pp 53-74. www.isteams/socialinformaticsjournal. dx.doi.org/10.22624/AIMS/SIJ/V10N1P7