Uninterrupted Service Research Articles

Improvement of Drug Stock Management Using ABC-VED Analysis in a University Hospital

Objective: Hospitals allocate approximately 35% of their budgets to pharmaceutical and material stocks in order to provide uninterrupted health services. For this reason, hospital managers spend a lot of time and effort in order to keep a minimum level of stock so as not to disrupt health service production and thus to better manage the limited resources of the enterprise. The aim of this study is to group the drugs according to their financial value and vital importance. In this way, it is aimed to perform stock management in the least costly, errorfree and effective way. Method: In the study, data corresponding to one-year (2021) consumption of a total of 1327 items of drugs were analyzed. The total cost is approximately 83 million ₺. In this study, an ABC-VED cross-analysis was performed on the one-year drug consumption data of a university hospital with 853 beds in order to provide an example of a more controlled inventory structure. Results: According to the results, it is seen that the ratio of drugs in the first category, that is, drugs that are both high cost and vital for the patient, to the total drug item is 38%. The cost of these drugs constitutes 87% of the total cost. Conclusion: Taking into account the classifications put forward in the study, strict monitoring of a small number of drugs and regular weekly counts will make drug stock management much easier for managers.

Design and implementation of a scalable IoT-based real-time environmental monitoring and alarm system: an experimental study

Digital transformation is crucial for organizations to survive, be competitive, and grow in the modern age. IoT is the key to enabling this transformation by connecting devices and optimizing processes. This paper presents the design and implementation of a generic IoT-based real-time environmental monitoring and alarm system. The platform is validated by applying it to a manufacturing plant scenario, where various sensors simulate industrial conditions. Scalable message distribution systems such as MQTT and Apache Kafka facilitate reliable data transmission. A microservice architecture is constructed for the backend services to ensure uninterrupted and high throughput services in the application domain. Instead of deploying a real WSN, traffic generation services were chosen to minimize costs, provide greater control and flexibility, and facilitate faster, scalable testing in a controlled environment. The platform also features an integrated alarm system with an event definition module, which allows users to define custom action rules. This flexible, scalable, and resilient architecture can be used across a wide range of application domains that require digital transformation. The experimental study demonstrates the platform's capabilities and great potential for broader IoT applications.

Investigating the transformative effect of technological and service innovations on postal sector adaptability during the pandemic Disruption in India

Purpose: This study aims to investigate the inventive adjustments that have been made to provide uninterrupted delivery services by the postal sector amidst the COVID-19 pandemic. Design/methodology/approach: This is an empirical study on the primary data collected from 354 postal users who use the services during and after pandemic disruption. This study uses regression, partial least square structural modeling and correlation to find out the relationship between dependent and independent variables. Originality/Value: This paper presents an empirical study that examines the determinants of innovation impacting customer satisfaction among postal users in India during the pandemic disruption, addressing the dearth of previous empirical research on the adaptability of the postal system in this context. The results of our study can help the postal sector create more effective strategies for utilizing cutting-edge logistics technology, enabling them to change into delivery service providers that are innovation-driven. Findings: The postal sector incorporates both service and technological innovation. The study also includes the other two constructs of logistics efficiency and customer satisfaction. Both service and technological innovation have a significant impact on customer satisfaction; however, service innovation is found to be the reason behind the survivability of the postal sector during the pandemic disruptive environment. Logistics efficiency positively affects customer satisfaction. However, logistics efficiency partially mediates the relationship between innovation and customer satisfaction. Overall, postal customers' satisfaction improves when innovation and logistics efficiency are present. Theoretical/methodological Contributions: This study connects innovation with logistics efficiency and customer satisfaction in the context of Indian postal system and their adaptability during COVID-19 Social/management Contributions: The impact of innovation on logistical efficiency and consumer perception can be better understood with the help of this study. This can then be used to formulate or adjust strategies to boost the India Post’s revenues and productivity.

Proactive self‐healing techniques for cloud computing: A systematic review

SummaryEnsuring the seamless operation of cloud computing services is paramount for meeting user demands and ensuring business continuity. Fault‐tolerant self‐healing techniques play a crucial role in enhancing the reliability and availability of cloud platforms, minimizing downtime and ensuring uninterrupted service delivery. This article systematically categorizes and analyzes existing research on fault‐tolerant self‐healing techniques published between 2005 and 2024. We provide a comprehensive technical taxonomy organizing self‐healing techniques based on fault tolerance processes, encompassing considerations for both reliability and availability. Additionally, we evaluate applications of proactive self‐healing techniques, highlighting their achievements, and limitations in enhancing service continuity. Strategies to address identified weaknesses are discussed, alongside future research challenges and open issues in the domain of cloud resilience. Through this analysis, the article contributes to understanding self‐healing techniques in cloud computing, offering insights into their effectiveness in ensuring service continuity. The findings aim to guide future research efforts in developing more robust and resilient cloud infrastructures, ultimately enhancing overall service reliability and availability. By emphasizing the importance of fault tolerance and self‐healing techniques, this article lays the foundation for advancing the state‐of‐the‐art in cloud computing.

5G enabled smart cities: A real-world evaluation and analysis of 5G using a pilot smart city application

Ubiquitous sensing in smart cities is expected to be one of the key beneficiaries of the high bandwidth and low latency capabilities of 5G. However, current 5G deployments still have low population coverage, and are unlikely to reach global coverage of above 80% before 2028. This means that new smart city applications are likely to experience a combination of 4G and 5G, limiting their data-intensive capabilities. Thus, it is necessary to assess the ability of current 5G deployments to support emerging smart city applications, and how they perform in 5G environments. Existing performance evaluations focus either on the 5G core or use instantaneous speed tests, which do not effectively assess the suitability of 5G deployments for smart city applications. In this paper, we present a comprehensive evaluation and analysis of real-world 5G network performance observed through the outcomes of a pilot smart city application, an innovative mobile 5G Internet of Things (IoT) solution to automatically identify and report road assets requiring maintenance. The pilot smart city application was deployed on 11 waste collection service trucks over a 6 month period (June 2022–Dec 2022). We undertook both application-specific and application independent network performance evaluation to assess the ability of the 5G deployment to support uninterrupted smart city services. Our analysis shows that while 5G is capable of supporting mobile video streaming applications, there are significant variations in network performance, which may make it unsuitable for applications that require higher data intensive or near real-time responsiveness.

Cardiac rehabilitation patient perspectives during COVID-19 pandemic: quantitative and qualitative study.

This study aimed to quantitatively assess stress, anxiety and obsessive thinking related to coronavirus disease-19 (COVID-19) and qualitatively appraise perceptions in patients after acute myocardial infarction (AMI) undergoing cardiac rehabilitation (CR) during the COVID-19 pandemic. We used mixed-methods design in patients referred for CR in 2 centres which delivered uninterrupted service during COVID-19 pandemic. Coronavirus Anxiety Scale (CAS), Obsession with COVID-19 Scale (OCS), COVID-19 Stress Scale (CSS), Hospital Anxiety and Depression Scale (HADS), and in-person interviews (combination of a priori questions and probing) were used to evaluate patient experience and perceptions with COVID-19 and the healthcare services during pandemic. In total, 109 patients (mean age 59 ± 10, 20% women) were included in quantitative part and in 30 of them we conducted the in-person interviews. About a quarter of patients met HADS threshold for anxiety and depression while CAS and OCS results demonstrated extremely low possibility of coronavirus related dysfunctional thinking (3%) and anxiety (2%). The CSS indicated the most prevalent concerns were related to COVID-19 vaccines safety (60%) and fear of getting infected (60%). During interviews, patients perceived the CR as well as health care providers as safe, trustworthy and with enough support to avoid or manage COVID-19 related health risks. Overall, patients reported AMI affected their lives more than the COVID-19 pandemic. The COVID-19 related stress and anxiety were relatively low and mostly related to general views of infectious disease. CR was perceived safe and trustworthy in terms of primary disease and COVID-19. This mixed-method study included 109 patients with acute myocardial infarction who underwent cardiac rehabilitation during the COVID-19 and focused on their experience and perceptions with COVID-19 and the healthcare services during pandemic.-Patients reported acute myocardial infarction affected their lives more than the COVID-19 pandemic.-The COVID-19 related concerns were mostly related to general views of infectious disease (vaccine safety, fear of getting infected) whilst cardiac rehabilitation was perceived safe and trustworthy environment during COVID-19.

Fatriot: Fault-tolerant MEC architecture for mission-critical systems using a SmartNIC

Multi-access edge computing (MEC), deploying cloud infrastructures proximate to end-devices and reducing latency, takes pivotal roles for mission-critical services such as smart grids, self-driving cars, and healthcare. Ensuring fault-tolerance is paramount for mission-critical services, as failures in these services can lead to fatal accidents and blackouts. However, the distributed nature of MEC architectures makes them more susceptible to failures than traditional cloud systems. Existing research in this field has focused on enhancing robustness to prevent failures in MEC systems rather than restoring them from failure conditions. To bridge this gap, we introduce Fatriot, a SmartNIC-based architecture designed to ensure fault-tolerance in MEC systems. Fatriot actively monitors for anomalies on MEC hosts and seamlessly redirects incoming service traffic to backup hosts upon detecting failures. Operating as a stand-alone solution on a SmartNIC, Fatriot guarantees the continuous operation of its fault-tolerance mechanism, even during severe errors (e.g., kernel failure) on the MEC host, maintaining uninterrupted service in mission-critical services. Our prototype of Fatriot, implemented on the NetFPGA-SUME, demonstrates effective mitigation of various failure scenarios, achieving this with minimal overhead to services (less than 1%).

Decomposition and reconstruction algorithms for IoT reliability analysis utilizing 5G technology for smart cities

Internet of Things (IoT) and 5G communication technologies in smart cities deliver promising services for heterogeneous applications. The application reliability banks on uninterrupted and seamless services experienced by the users. However, the increasing smart city application demands influence the experience reliability through augmented wait times. This article therefore introduces a Coherent Reliability Service Broadcasting Technique (CRSBT) for sustaining constructive application services. This technique incorporates linear regressive and digressive learning for application service improvements and restrictions. Based on the demand, the regressive process verifies the wait time and with the reducing demands, the service broadcast ratio is verified. These two factors are verified post the demand and response through 5G resource allocations and IoT computations. Both the service-oriented features are validated for regressive service broadcast and either of the one is used for digressive response. The coherence between the computations (IoT) and resources (5G) is verified on-demand and linearly. Therefore, the proposed technique is reliable in sustaining service broadcast, less wait time, and maximum flexibility.

Optimal Guard Channel Reservation and its Comparison with Fractional Channel Policies in Mobile Cellular Network

In the current communication era, 2G voice services coexist with higher generation mobile network voice services like Voice over Long Term Evolution (VoLTE) in 4G and Voice over New Radio (VoNR) in 5G. Subscribers registered in the 5G network, but their voice option is in 4G so voice calls can be handled through the Evolved Packet System (EPS) Fallback or Radio access technology (RAT) Fallback. Similarly, subscribers register in a 4G network, but their voice option is in 3G or 2G so voice calls can be handled through Circuit Switched Fallback (CSFB). To provide uninterrupted voice service in such wireless networks usually handoff calls (HCs) receive higher priority than new calls (NCs). So, some guard radio resources (i.e., channels in 2G or RBs in 4G or 5G) may be reserved in each cell to handle this type of HCs. If more channels are reserved for HCs, then the handoff call-dropping probability (HCDP) will be decreased and at that time the new call-blocking probability (NCBP) will be increased. So, by considering the target HCDP if channels are reserved for HC, then HCDP will remain below the target and NCBP will be minimum. In this paper first, we proposed an optimal channel reservation (OCR) policy that reserves guard channels according to the given target HCDP. Second, we compared our OCR policy with fractional channel (FC), limited fractional channel (LFC), and uniform fractional channel (UFC) policies. Finally, we observed the performance of all these policies considering the Global System for the Mobile Communication (GSM) network.

Processing and classifying IP packet data on the Internet based on machine learning

Nowadays, the continuous development of information technology, communication over the Internet is increasing rapidly, and network congestion has become an alarming issue. To develop communication network infrastructure in a large city, a country, or globally, streamlining and controlling network data flow to optimize communication processes and minimize network congestion is crucial and necessary. In this study, the authors analyze and process data according to the delay of Internet Protocol (IP) packets, using machine learning models with the Random Forest (RF) and the Support Vector Machines (SVM) method to classify IP packets. The primary goal of classifying packets by delay is to optimize network performance by prioritizing processing of low-delay packets, ensuring stable and uninterrupted online services such as video streaming and voice calls. Furthermore, it is easy to manage and control packet traffic, hence minimizing network congestion at the router. ® 2024 Journal of Science and Technology - NTTU

Strategic Planning for Post-Earthquake Health Services Continuity: Leveraging Family Healthcare Centers in Istanbul

Abstract Earthquakes, known for their widespread devastation, annually inflict catastrophic consequences globally. Swift and well-structured healthcare responses following earthquakes are pivotal in reducing their impact and mitigating loss of life. However, achieving this demands proactive strategic planning and effective preparedness before disaster strikes. While countries craft disaster response plans, their implementation often proves inadequate in managing the ensuing crisis comprehensively. This study proposes a paradigm shift by advocating for the utilization of widely accessible Family Health Centers (FHCs) as crucial hubs for post-earthquake healthcare continuity. Focused on these community-centric health units, our research delineates a strategic blueprint ensuring uninterrupted health services post an Istanbul earthquake. Integrating SWOT analysis, balanced scorecard, and operations research, this study holistically assesses the current landscape of FHCs and identifies imperative post-earthquake requisites. Insights gleaned from extensive literature review and expert consultations underpin this multifaceted approach.

The generator distribution problem for base stations during emergency power outage: A branch-and-price-and-cut approach

Motivated by the need for uninterrupted service provision in the telecommunications industry, this paper presents a novel problem concerning the transportation of diesel generators during an unplanned power outage. Given a set of base stations, each equipped with a capacitated back-up battery pack, the problem consists in finding an optimal delivery and pick-up schedule that minimises corresponding costs. The problem is significantly complicated by the fact that the delivery quantity is a decision variable, and the pick-up times depend on the delivery time, delivery quantity and constraints related to battery-charging requirements. To address the issue, we develop problem-specific pick-up time functions that can be effectively incorporated into the proposed algorithm. The problem is formulated as an arc-based model and a set-packing model. To solve it to optimality, we design a tailored branch-and-price-and-cut algorithm, including novel customised dominance criteria in the labelling algorithm and adopting heuristics that exploit the problem features and effectively improve the algorithmic performance. The efficacy of the proposed algorithm is validated based on the extensive computational study and compared with a commercial solver. The proposed acceleration techniques are found to be potent with regard to computational times, and useful managerial insights are provided as part of sensitivity analyses.

Paramedics’ experiences of barriers to, and enablers of, responding to suspected or confirmed COVID-19 cases: a qualitative study

BackgroundParamedics’ work, even pre-pandemic, can be confronting and dangerous. As pandemics add extra stressors, the study explored paramedics’ lived experience of the barriers to, and enablers of, responding to suspected or confirmed Coronavirus Disease 2019 (COVID-19) cases.MethodsThis exploratory-descriptive qualitative study used semi-structured interviews to investigate Queensland metropolitan paramedics’ experiences of responding to cases during the COVID-19 pandemic. Interview transcripts were analysed using thematic analysis. Registered Paramedics were recruited by criterion sampling of staff who experienced the COVID-19 pandemic as active officers.ResultsNine registered paramedics participated. Five themes emerged: communication, fear and risk, work-related protective factors, leadership, and change. Unique barriers included impacts on effective communication due to the mobile nature of paramedicine, inconsistent policies/procedures between different healthcare facilities, dispatch of incorrect information to paramedics, assisting people to navigate the changing healthcare system, and wearing personal protective equipment in hot, humid environments. A lower perceived risk from COVID-19, and increased empathy after recovering from COVID-19 were unique enablers.ConclusionsThis study uncovered barriers and enablers to attending suspected or confirmed COVID-19 cases unique to paramedicine, often stemming from the mobile nature of prehospital care, and identifies the need for further research in paramedicine post-pandemic to better understand how paramedics can be supported during public health emergencies to ensure uninterrupted ambulance service delivery.

The evolution of technology and the transformation of the banking sector under the influence of digital trends

Banks have been using technology for decades to improve their operations. However, the pace of digital transformation has accelerated in recent years.The impact of digital transformation on the banking sector is very significant. Traditional banks must adapt to the changing digital landscape or risk losing customers to more digitally savvy competitors. One of the most significant consequences of digital transformation for ordinary banks is the change in customer expectations. Now customers expect uninterrupted and efficient banking services through all channels, including digital ones. This forces ordinary banks to invest in digital technologies in order to remain competitive.Another impact of digital transformation on conventional banks is the change in the way banks interact with customers. In the past, banks used physical branches as the main means of interacting with customers. Something more is needed to remain competitive. Banks now have to interact with customers through several channels, including mobile apps, online portals and chatbots.All these and many other digital innovations are transforming the banking sector and necessitate the study of these phenomena.

Day-ahead resilience-economic energy management and feeder reconfiguration of a CCHP-based microgrid, considering flexibility of supply

Many challenges have emerged due to the intense integration of renewables in the distribution system and the associated uncertainties in power generation. Consequently, local management strategies are developed at the distribution level, leading to the emergence of concepts such as microgrids. Microgrids include a variety of heating, cooling, and electrical resources and loads, and the operators' aim is to minimize operation and outage costs. Since significant distribution system outages are typically caused by events such as earthquakes, floods, and hurricanes, microgrid operators are compelled to improve resilience to ensure uninterrupted service during such conditions. A mixed-integer linear programming model is designed in this paper to optimize the energy management and structural configuration of microgrids. This optimization aims to enhance resilience cost, minimizing operation and capital costs as well as power loss and pollution. To achieve these goals, several tools are implemented including reconfiguration, storages, combined cooling, heat and power units, wind turbines, photovoltaic panels, as well as capacitors. Four case studies are defined to prove the developed model efficiency. The first case study focuses on energy management in the microgrid for operation cost minimization. The second case study emphasizes the improvement of resilience alongside energy management, aiming at minimizing costs and enhance resilience. In the third case, the microgrid's reconfiguration capability is also added to the second case. Therefore, this case aims to optimize both energy and structural management within the microgrid to simultaneously enhance resilience and minimize operational costs. Finally, in the fourth case, the problem is studied in a multi-objective approach. By comparing the results, the resilience impact on the operation of microgrids is elucidated. By considering the resilience concept in microgrid operation and based on the results of case 2, it is found that the operating costs are increased by an average of 10.38 %. However, because of reducing resilience costs by an average of 13.91 %, the total cost is reduced by an average of 5.93 % in case 2 compared to case 1. Furthermore, when comparing cases 2 and 3, the reconfiguration effect can be determined. It can be observed that the operating costs are decreased by an average of 4.5 %. Moreover, the resilience cost is decreased by an average of 1.61 %, resulting in an overall reduction of the total objective function by an average of 2.43 % in case 3 compared to case 2.

The Resilience of Electrical Support in UAV Swarms in Special Missions

Unmanned aerial vehicle (UAV) swarms serve as a dynamic platform for diverse missions, including communication relays, search and rescue operations, and environmental monitoring. The success of these operations crucially depends on the resilience of their electrical support systems, especially in terms of battery management. This paper examines the reliability of electrical support for UAV swarms engaged in missions that require prioritization into high and low categories. The paper proposes a dynamic resource allocation strategy that permits the flexible reassignment of drones across different-priority tasks, ensuring continuous operation while optimizing resource use. By leveraging the Markov chain theory, an analytical model for the evaluation of the resilience of the battery management system under different operational scenarios was developed. The paper quantitatively assesses the impact of different operational strategies and battery management approaches on the overall system resilience and mission efficacy. This approach aims to ensure uninterrupted service delivery for critical tasks while optimizing the overall utilization of available electrical resources. Through modeling and analytical evaluations, the paper quantifies the impact of various parameters and operating strategies on overall system resilience and mission availability, considering the utilization strategies of batteries and their reliability and maintenance metrics. The developed models and strategies can inform the development of robust battery management protocols, resource allocation algorithms, and mission planning frameworks, ultimately enhancing the operational availability and effectiveness of UAV swarms in critical special missions.

A BLOCKCHAIN FRAMEWORK FOR SMART AND CYBER-RESILIENT CITIES

The transition of urban environments into smart cities brings forth unprecedented challenges and vulnerabilities in the face of cyber threats. In response, this study presents a pioneering Blockchain Framework tailored to fortify smart cities against evolving cyber risks. Embracing decentralization and immutability inherent in blockchain technology, the framework addresses the shortcomings of centralized systems, thereby enhancing security and resilience. The primary objective of the framework is to in still trust, mitigate cyber risks, and ensure uninterrupted services within the dynamic urban landscape. By leveraging blockchain's distributed ledger capabilities, the framework establishes a robust foundation for securely managing and validating critical urban data and transactions. Furthermore, its decentralized architecture minimizes single points of failure, reducing the susceptibility of smart city infrastructures to malicious attacks and disruptions. This innovative approach represents a significant stride towards the development of cyber-resilient infrastructures for smart cities, safeguarding against potential threats and vulnerabilities. By fostering trust, bolstering security measures, and promoting continuity of services, the Blockchain Framework serves as a cornerstone in fortifying the resilience of modern urban environments amidst the rapid pace of technological advancement and urbanization. Keywords: Mitigate Cyber Risks , Blockchain Framework , Smart cities , Dynamic urban landscape

Leveraging Distributed Systems for Fault-Tolerant Cloud Computing: A Review of Strategies and Frameworks

Ensuring system availability and reliability is crucial in the quickly developing field of cloud computing. The importance of fault tolerance in cloud infrastructure systems grows as organizations become more reliant on it to support their critical operations. The purpose of this article is to investigate the intricate realm of cloud computing and distributed systems. Specifically, the paper will investigate the numerous forms of cloud computing, fault tolerance methods, and frameworks that enable cloud services to be robust and durable. Cloud computing has transformed the way in which organizations and individuals access and administer computing resources. The paper discusses several deployment options, including public, private, hybrid, and multi-cloud environments, which provide organizations with the advantages of flexibility, scalability, and cost-effectiveness. The inherent flexibility of cloud computing renders it well-suited for a diverse range of applications, spanning from the hosting of websites to the execution of intricate data analytics processes. Generally, cloud computing encounters substantial obstacles, including the need of maintaining uninterrupted service in the face of hardware failures, network outages, or software errors, despite its tremendous benefits. The critical importance of fault tolerance in this particular situation cannot be overstated, as it plays a pivotal role in maintaining the dependability and availability of the system. The primary objective of this study is to examine the utilization of distributed systems as a means to augment fault tolerance within the realm of cloud computing and distributed systems. Distributed systems offer an optimal approach for addressing difficulties related to fault tolerance, owing to its intrinsic capability to divide workloads and data over several nodes. This approach utilizes redundancy, replication, and the ability to recover seamlessly from disturbances, hence enhancing the resilience and resource efficiency of cloud services. This research reviews novel techniques and frameworks that utilize distributed systems to create fault-tolerant cloud computing architectures, emphasizing their substantial influence on the cloud computing domain. In conclusion, this research report includes a comparative analysis table that encompasses twenty preceding works.

Forensic, medical and legal problems and solutions on passenger and cargo ships

Marine vehicles have an important place in international trade and tourism. There are various directives and studies on the prevention of health problems in marine vessels and injuries and deaths due to occupational accidents. In the literature, not enough studies have been found in which the issues to be considered in cases of injuries, sexual assaults, accidents, suicides and murders that are common in forensic medicine practice, and there are no guidelines or recommendations of internationally accepted organizations. It is important to determine the seafarer who is responsible for intervening in health emergencies on cargo ships, and to detect faulty ones, if any, in work accidents that result in serious injury and death. In addition, injuries, suicides and murders are encountered among the crew, and crime scene findings are lost until they are evaluated by the judicial authorities. Although rare, sexual assaults on cargo ships are also reported, but there are not enough scientific studies that indicate what should be done in terms of evidence evaluation. Our study emphasizes the issues to be considered, that one of the crew should be held responsible and necessary training should be given in order to make a forensic medical evaluation in forensic events that will be encountered on cargo ships, and that physicians and health workers should be competent in the first forensic medical evaluation in case of emergency on passenger ships. It is thought that the launch of the telemedicine application, which provides uninterrupted service for forensic medical emergencies in maritime vessels, under the leadership of organizations such as the “International Maritime Organization” (IMO), will make a significant contribution. In addition, suggestions are made for legal impasses in such cases that take place in high seas.

Detection and analysis of cellular network traffic anomalies and SMS spammers

The unfolding usage of mobile users inclusive of both 4G and 5G creates huge accumulation of data in cellular network. The network service providers need to ensure proper management of resource in terms of uninterrupted service with cost-effectiveness. The detection of cellular traffic and Short Message Service (SMS) spammers is very challenging. In this paper a novel method is proposed to analyse and detect the traffic anomalies and SMS spammers. To achieve this, Call Detail Record (CDR) issued by service provider is used. The CDR is pre-processed to convert into machine understandable format using mean-normalization technique. K-means clustering elbow method proves to be the best tool in identifying the traffic clusters in the network that detects both high and low traffic in the network. The novelty of the proposed work is the detection of low traffic clusters which usually is misled as sleeping cell or cell outage. The paper also presents a model designed to predict whether the message is spam SMS or ham SMS. The proposed model is suitable to run different classifiers like Logistic Regression, Multi nominal Naive Bayes, Support Vector Machine (SVM), Random Forest Classifier. The model gives the highest accuracy rate of 98.277% with SVM in detecting SMS spam.