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Analytics Enabled Decision Making Tracing the Journey from Data to Decisions
In the current business environment, which is greatly dynamic and competitive, business organizations are continually striving for expanding their competence and financial performance through improving almost every facet of their business--product/service quality, customer satisfaction, customer retention, productivity, line filling strategies, and others. In this sense, success and failure of organizations depend on the extent of precision of their decisions. Organizations are engaged with data to extract insights, identify trends and make decisions at different levels; and also, many of them learn how to utilize the power of data. Analytics can enable them to derive conclusions, make predictions, and ascertain actionable insights in a contextual and time-bound manner. It helps to examine data from multiple perspectives and gives visualizations by using different frameworks and platforms such as IBM Watson, Tableau, and R. The chapter presents the role of analytics in decision-making processes and assess the effectiveness of decisions upon their implementation, so the corrective measures can also be inserted. As decision making is a continuous business process, analytics accelerates it and gives organizations a pace to keep updated with changing business scenarios. Thus, this chapter presented a decision-making framework exhibiting how decision-making functions as an ongoing process. Different contexts and cases have been used to establish the relevance of each step of the framework. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Analytics Enabled Decision Making
Analytics is changing the landscape of businesses across sectors globally. This has led to the stimulation of interest of scholars and practitioners worldwide in this domain. The emergence of big data, has fanned the usages of machine learning techniques and the acceptance of Analytics Enabled Decision Making. This book provides a holistic theoretical perspective combined with the application of such theories by drawing on the experiences of industry professionals and academicians from around the world. The book discusses several paradigms including pattern mining, clustering, classification, and data analysis to name a few. The main objective of this book is to offer insight into the process of decision-making that is accelerated and made more precise with the help of analytics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Analytical study of triple diffusive convection in a bi-viscous Bingham fluid layer using Ginzburg-Landau model
In this paper, considering bi-viscous Bingham as the base fluid, we study the thermophysical-properties (such as density, specific heat, thermal conductivity, thermal diffusivity, and thermal expansion) with different combinations of salts among NaCl, KCl, CaCl2, and NaCl2 of triple diffusive convection in a bi-viscous Bingham fluid layer with heat as one of the diffusing components. A weakly non-linear case is formulated to facilitate a solution to the problem using a series solution Ginzburg-Landau model. With regard to single, double, and triple diffusive convection, the tables are made to record the actual values of thermophysical-properties together with the critical Rayleigh-number for each combination of aqueous-salt solutions. This computation calculates the mean Nusselt and Sherwood numbers to quantify the systems heat- and mass-transfers for various aqueous-solutions. The effect of the bi-viscous Bingham fluid parameter, for small and large values, for different aqueous-solutions, in single, double, and triple diffusive convection has been captured via 2-dimensional (2D) and 3-dimensional (3D) figures and the results are recorded and compared. The investigation reveals that the heat- and mass-transfers increase with an increase or decrease in the bi-viscous Bingham fluid parameter, which in turn depends on the values of (Formula presented.) and (Formula presented.) The results confirm that the heat- and mass-transfers are least for the combination of KCl with CaCl2 and maximum for the combination of NaCl with other salts. 2024 Taylor & Francis Group, LLC. -
Analytical study of triple diffusive convection in a bi-viscous Bingham fluid layer using Ginzburg-Landau model
In this paper, considering bi-viscous Bingham as the base fluid, we study the thermophysical-properties (such as density, specific heat, thermal conductivity, thermal diffusivity, and thermal expansion) with different combinations of salts among NaCl, KCl, CaCl2, and NaCl2 of triple diffusive convection in a bi-viscous Bingham fluid layer with heat as one of the diffusing components. A weakly non-linear case is formulated to facilitate a solution to the problem using a series solution Ginzburg-Landau model. With regard to single, double, and triple diffusive convection, the tables are made to record the actual values of thermophysical-properties together with the critical Rayleigh-number for each combination of aqueous-salt solutions. This computation calculates the mean Nusselt and Sherwood numbers to quantify the systems heat- and mass-transfers for various aqueous-solutions. The effect of the bi-viscous Bingham fluid parameter, for small and large values, for different aqueous-solutions, in single, double, and triple diffusive convection has been captured via 2-dimensional (2D) and 3-dimensional (3D) figures and the results are recorded and compared. The investigation reveals that the heat- and mass-transfers increase with an increase or decrease in the bi-viscous Bingham fluid parameter, which in turn depends on the values of (Formula presented.) and (Formula presented.) The results confirm that the heat- and mass-transfers are least for the combination of KCl with CaCl2 and maximum for the combination of NaCl with other salts. 2024 Taylor & Francis Group, LLC. -
Analytical Study of Security Enhancement Methods on Diverse Cloud Computing Platforms
Cloud storage is a convenient and virtually limitless storage option for the bulk of data technology is producing in recent times. Data security in cloud is not so robust as data owners need to depend upon the service providers for the safe storage. In this paper, we have identified few broadly used cloud computing paradigms: mobile cloud, cloud-based IoT and multi-tenant cloud. Mobile cloud helps reduce the data storage overhead on the mobile device and give users access to their personal data as and when required through cloud access. Cloud-based IoT helps the network of IoT devices, which is growing exponentially, to create on-demand cloud repositories. Multi-tenant cloud platforms are cloud environment accessed by more than one user. Few recent and related research work which aims at enhanced security from all these three paradigms is discussed and analysed. Encryption and similar network securing methods are used for mobile cloud and cloud-based IoT. For multi-tenant cloud, the objective is to keep the user spaces separate to keep their resources confidential. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analytical study of BrinkmanBard convection in a bidisperse porous medium: Linear and weakly nonlinear study
Linear and weakly nonlinear stability analyses of BrinkmanBard convection of a Newtonian fluid saturating a bidisperse porous medium (BDPM) are made. Local-thermal-non-equilibrium (LTNE) is assumed between the fluid and the porous spheres (micro-pores) that make up the macro porous medium. Two coupled linear momentum equations are considered one each for the macro- and micro-pores. Results of mono-disperse porous medium (MDPM) with solid spheres are recovered as a limiting case of the present study. Further, in the case of both types of porous media considered the results of DarcyBard and BrinkmanBard convection are extracted under suitable limiting procedures. To keep the work analytical, we reduce the intractable hexa-modal Lorenz model with four quadratic nonlinearities into the tractable mono-modal StuartLandau equation (SLE) with cubic and quintic nonlinearities. Subcritical instability is discounted in the study thereby suggesting that cubic SLE and cubicquintic SLE both expound similar results qualitatively. The concept of a BDPM is shown to be meaningful only when the pores are not large, and when they are very small, then the MDPM assumption applies. Similar observation can be made when the ratio of permeabilities is large. The presence of micro-pores does not alter the size of the convective cell significantly at the onset. The present study reiterates the findings of several earlier works. 2023 Elsevier Ltd -
Analytical Studies on Metal Complexes in Solution
Analytical chemistry is the study of separation, identification and quantification of the chemical components of natural and artificial materials. Mainly analytical chemistry deals with quantitative and qualitative analysis. It has applications in chemistry, biochemistry, biology, geology and other sciences and also in industries. Many analytical methods occupy a unique position because of its simplicity, less expensive instrumentation, high sensitivity and selectivity. A great development in spectrophotometry is based on development and measurement of colour. Molecules which do not give colour by themselves develop appreciable colour on reaction with chromogenic reagents and provide a method of analytical determination of molecules. So efforts are being directed towards finding suitable reagents, which have characteristic absorption with metal ions in spectrophotometric analysis. Molybdenum and vanadium are important elements both for industry and for biological systems The simultaneous determination of these metal ions in various samples are of great importance. Therefore efforts are being directed towards finding suitable reagents, which have characteristic colour reactions with microgram amounts of metal ions of interest for spectrophotometric analysis. Salicylaldehydep-chlorophenyl thiosemicarbazone(SAPCPTSC) as a chromogenic reagent for the extractive spectrophotometric determination of Vanadium(V) and Molybdenum(VI) is presented in this study. The reagent SAPCPSC gave instantaneous and stable yellow colour with Vanadium(V) and Molybdenum(VI) in the acidic pH range. The colour reactions in detail has been explored and the possibility of spectrophotometric determination of the micro amounts of vanadium(V) and molybdenum(VI) is established with necessary conditions. The stoichiometry of the complex is established by Jobs method of continuous variation and confirmed by mole ratio method. The stability constant, the standard deviation and the coefficient of variations are reported. Derivative spectrophotometry enables the exact determination ?maxof this type of metal ions. Molar absorptivity, Sandells sensitivity and quantitation limit values show that the proposed method is highly sensitive. The coloured species were stable over several hours making the method practicable. Many cations and anions do not interfere with the determination even if they are present in excess. Surfactants have the ability to solubilise a water insoluble complex or ligands and so micellar medium has also been employed so as to avoid the use of toxic organic solvents. The proposed method has been successfully applied for the determination of molybdenum and vanadium in steel samples.KEY WORDS: Salicylaldehydep-chloroanilinethiosemicarbazone, vanadium, molybdenum, derivative spectrophotometry, micellar medium, simultaneous determination. KEY WORDS: Salicylaldehydep-chloroanilinethiosemicarbazone, vanadium, molybdenum, derivative spectrophotometry, micellar medium, simultaneous determination. -
Analytical Results of Heart Attack Prediction Using Data Mining Techniques
In the modern era of living a fast lifestyle, people are not more conscious of their food eating and lifestyle. Due to these reasons, the chances of having a cardiac-related disease have risen drastically. This paper has studied the various supervised and unsupervised machine learning algorithms in comparative methods with best accuracy. Models like classification algorithms, regression algorithms, and clustering algorithms have been used for this paper. This research paper majorly focuses on patients with certain medical attributes that indicate a higher risk of heart disease. The model almost gives a good accuracy for all the regression and classification models when compared to the clustering models. Among all the algorithms, random forest and decision tree gives better accuracy 2023 IEEE. -
Analytical modeling of reconfigurable transistors
A functionally enhanced transistor is a potential candidate for further advancing electronics and Moore's law beyond the classical scaling. This chapter discusses these kinds of multifunctional transistors called reconfigurable field-effect transistor (RFET) and reconfigurable tunnel field-effect transistor (RTFET). The RFET works on the principle of Schottky barrier tunneling, and the RTFET works on the principle of band-to-band tunneling. Both devices can be configured as an n-type and p-type device based on the biasing. This chapter explains the working and performance comparison of RFET and RTFET in detail with the help of technology computer-aided design (TCAD) simulations. Further, the potential and current models of a single-gated RFET and double-gated RTFET are presented in this chapter. The presented analytical models are compared and verified with TCAD simulations. The potential in the channel regions of RFET and RTFET is modeled by solving a two-dimensional (2D) Poisson's equation. Because the working principle of both devices is different, two different formulas are utilized for modeling the current in the device. The current model for the RFET is developed by integrating Landauer's formula, whereas the current model for RTFET is obtained by integrating band-to-band generation rate over the tunneling volume. The procedure, technique, and assumptions followed to obtain the potential and current models of RFET and RTFET are detailed in this chapter. 2022 selection and editorial matter, Ashish Raman, Deep Shekhar and Naveen Kumar; individual chapters, the contributors. -
Analytical Methods of Machine Learning Model for E-Commerce Sales Analysis and Prediction
In the commercial market, E-commerce sales show a significant trend and have attracted many consumers. Ecommerce sales forecasting has a significant role in an organization's growth and aids in improved operation. Many studies have been conducted in the past using statistical, fundamental, and data mining techniques for better analysis and prediction of sales. However, the current scenario calls for a better study that combines the available information to propose different machine-learning techniques. The sole motive of the study is to analyze and determine different machine learning models to predict accurate results. The research observed that the Extreme Gradient Boosting model outperformed all other models and brought a good result. It produced an RMSE value of 0.0004 and Explained Variance score of 0.99. Decision Tree algorithm also shows an exemplary result. 2023 IEEE. -
ANALYTICAL METHODS FOR TRAMADOL IN PHARMACEUTICAL AND FORENSIC CONTEXT A REVIEW
Tramadol is a centrally-acting weak opioid recept or analgesic and is a racemic mixture of (+)-tramadol and ()-tramadol enantiomers. Tramadol does not show many adverse severe effects without any dependency potential in therapeutic doses, as seen in other opioids only if not used for extended periods in doses higher than recommended. Symptoms of tramadol intoxication are similar to those of other opioid analgesics but may include serotonergic and noradrenergic components. Fatal intoxications are rare and appear synergetic with other drugs and alcohol. There is growing evidence of abuse of tramadol in many countries. Due to its extensive use in the medical field as an analgesic of choice, pharmaceutical analysis in both process and quality control is essential. Due to its abuse and overdose cases, forensic toxicological analysis of tramadol in body fluids and tissues is also vital in medico-legal practice. Tramadol and its metabolites are found in wastewater also. This analytical review (from 2016-2021) focuses on identifying and determining t ramadol in bulk dr ugs, formulations, forensic drug seizures, forensic toxicological specimens, and wastewater. The analytical methods covered include UV/Visible/IR spectrophotometric methods, thin-l ayer, gas and li quid chromat ographic met hods, electrochemical methods, GC-MS, LC-MS, LC-MS-MS methods, and electrochemical methods. The review will i nt eres t phar maceut i cal chemi st s, pharmacol ogis ts, biochemists, forensic chemists, forensic toxicologists, and environmental scientists. 2023, Medico Legal Society. All rights reserved. -
Analytical investigation of heat transfer in multilayer human eye based on dual-phase-lag thermoelastic theory
Thermal damage to ocular tissues is a critical medical concern because even small temperature elevations can impair corneal endothelial function, accelerate cataract formation, and disrupt retinal metabolism. This issue is particularly relevant in regions with intense thermal environments, such as Saudi Arabia, where preventive health care and advanced biomedicalfacilities are required. This study develops a predictive framework for estimating temperature distributions within the human eye under external heat exposure. A dual-phase-lag (DPL) bioheat transfer model incorporating two thermal relaxation times is formulated to capture finite speed thermal wave propagation in the multilayer structure of the eye, and closed-form analytical solutions are obtained using a normal mode approach. A mechanics-informed machine learning surrogate model is then constructed using data generated from the analytical DPL solutions, enabling rapid prediction of intraocular temperature across the parameter space. Parametric investigations examine the effects of ambient temperature, evaporation rate, tissue porosity, and blood perfusion on the thermal response of the six ocular layers. Comparisons with the LordShulman and classical Fourier models reveal important differences in predicted temperature behavior under non-Fourier heat transfer. Additional analysesincluding thermal safety mapping, sensitivity assessment, and response surface visualizationprovide further insight into the combined influence of environmental and physiological parameters. The results show that non-Fourier thermal effects significantly influence peak intraocular temperature, while ambient temperature and evaporation dominate anterior eye heating and perfusion primarily affects deeper tissues. The present model assumes axisymmetric geometry and temperature-independent material properties, which may be extended in future studies using three-dimensional or patient-specific models. Overall, the proposed hybrid analyticalmachine learning framework provides an efficient tool for ocular thermal risk assessment and supports the development of preventive strategies for populations exposed to extreme thermal environments. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026. -
Analytical Estimation and Experimental Validation of the Bending Stiffness of the Transmission Line Conductors
The bending stiffness of transmission line conductors can vary significantly, ranging from maximum stiffness when behaving monolithically to minimum stiffness when wires behave loosely. This large range makes it challenging to estimate stiffness accurately at intermittent bending stages. To address this issue, a mathematical model that accounts for both frictional forces between wires in the same layer and the clenching effects of helical wires from preceding layers is proposed in this paper. The proposed model estimates cable bending stiffness as a function of axial load and curvature for multilayered strands by considering slip caused by wire behavior. To evaluate the bending stiffness, experiments were conducted on Panther and Moose Indian Power Transmission line conductors. The proposed slip model considers Coulomb frictional effects and clenching effects caused by Hertzian contact forces, filling the void in the estimation procedure. Additionally, the model considers the wire stretch effect, a parameter not previously accounted for in cable research. The predicted numerical results of the proposed model were found to vary within a maximum of 7% from the experimental tests. The proposed mathematical model thus offers a more accurate and comprehensive way of estimating the bending stiffness of transmission line conductors, addressing the existing limitations in the estimation procedure. 2024 College of Engineering, Universiti Teknologi MARA (UiTM), Malaysia. -
Analytical and AINN-based investigation of surface wave propagation in dry long bones with initial stress, magnetic field, and rotation effects
This study presents a comprehensive analytical and artificial intelligence neural network (AINN)-based investigation of wave propagation in dry long bones, modeled as an orthotropic hollow cylindrical structure. The proposed model incorporates the combined effects of initial stress, magnetic field, and rotational motion to capture the complex behavior of bone-like media under coupled physical influences. The governing equations are formulated within a continuum mechanics framework and solved analytically using displacement potential methods, yielding solutions in terms of Bessel functions that satisfy the cylindrical geometry and boundary conditions. Two distinct cases, corresponding to the absence and presence of rotation, are examined to assess the influence of rotational effects on wave dynamics. A detailed parametric analysis is carried out to evaluate the variation of phase velocity and frequency with respect to wave number, initial stress, magnetic parameter, density, and geometric ratios. The analytical results indicate that initial stress enhances wave propagation, while magnetic effects introduce damping and rotation significantly modifies dispersion characteristics. To improve computational efficiency and predictive capability, an AINN model is developed and trained using analytically generated data. The AINN predictions show excellent agreement with the analytical results, as confirmed through parity plots, error analysis, residual distribution, and loss convergence behavior. The novelty of the study lies in the unified analytical-AINN framework that integrates mechanical, electromagnetic, and rotational effects within a single model. The findings provide important insights for wave-based characterization of bone structures and have potential applications in non-destructive evaluation, ultrasonic diagnostics, and advanced biomedical sensing systems. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026. -
ANALYSIS, ASSESSMENT, AND MANAGEMENT OF ENVIRONMENTAL AIR POLLUTION USING ENVIRONMENTAL ENGINEERING IN DEVELOPING COUNTRIES
Recent studies underscore the value of contemporary technology and gas emissions mitigation while overlooking the necessity of optimal fuel in Developing Countries (DC). DC's historical economic expansion has significantly depended on fossil fuels, resulting in severe environmental air pollution (EAP) challenges. The separation of economic progress from pollution has been the central emphasis in advancing environmental civilization in emerging countries. This study presents an analysis, assessment, and management of EAP using environmental engineering (EE) in DC. This work has examined the evolution of EAP regulations in DC, emphasizing a strategic shift from emission regulation to Air Quality Management (AQM). The regulation of Sulfur dioxide (SO2) emissions addressed the worsening of acid rain in DC. Since 2015, regulatory measures across several sources and industries have aimed to decrease the total amount of Fine Particulate Matter (FPM2.5), signifying a shift towards an AQM-focused policy. Escalating ozone (O3) pollution necessitates integrated management measures for O3 and FPM2.5, focusing on their intricate photochemical reactions. Significant enhancement of AQM in DC, as a crucial metric for the efficacy of sustainable economic development, necessitates the profound carbon reduction of the DC's energy infrastructure and the establishment of more integrated strategies to tackle EAP and climate change in DC concurrently. 2024, Rotherham Academic Press Ltd. All rights reserved. -
Analysis using a modified Johnsoncook model for AISI 304 stainless steel and ofprior dynamic tensile behavior deformed AISI type 304 stainless steel
304 stainless austenitic steel (AISI 304) is renowned for its high temperature resistance and has been the subject of considerable research. To explore its rheological behavior at high temperature, isothermal hot compression experiments were conducted on the Gleeble-3800 thermal simulator at temperatures of 8001200 C, strain rates of 0.01111 s-1, and a total strain of 60%. From the experimental data, a JohnsonCook (JC) constitutive model was formulated and further optimized. The optimized model considers the combined effect of strain, strain rate, and temperature, resulting in a more precise constitutive equation. The enhanced JC model had excellent predictive power, with a correlation coefficient (Rco) of 0.9884 and an average absolute relative error (AARE) of 8.42%. ABAQUS simulations for verification confirmed the model to be valid. This study offers valuable theoretical information for the hot working of SS 304, enabling more precise predictions of stress behavior at high temperature and easier optimization of processing parameters and overall material behavior. Also, deformation of metastable austenitic stainless steel at temperatures below the Md point leads to the transformation of austenite into martensite. This study investigates how prior deformation, conducted at temperatures both below and above Md, affects the dynamic tensile behavior of AISI 304 stainless steel. Pre-deformation at 25C (below Md), as well as at elevated temperatures of 200C and 300C (above Md), enhances both the yield strength and ultimate tensile strength of the material. Notably, prior deformation at 25C to a small equivalent strain (< 0.03) results in significant improvements in strength (22%) and ductility (2137%) during subsequent high strain-rate tensile loading at 200 and 300s?1. The evolution of local strain fields and strain rates is analyzed using digital image correlation. Additionally, the development of localized necking is investigated through in-situ high-speed camera imaging. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025. -
Analysis on thermal sensitivity of 2D Profilometer used for TMT Glass Polishing
TMT adopts Stressed Mirror Polishing (SMP) technology for the polishing of mirror segments. In this process, the meniscus type spherical shape glass blanks are converted in to a desired aspheric shape by spherical grinding and polishing in the stressed condition. After each grinding and polishing activity metrological measurements are done using different metrology tools. The metrology tool named as 2D-Profilometer is used for low frequency error/foam measurements. It consists of 61 high precision length gauges attached to Carbon Fiber Reinforced Polymer (CFRP) sandwiched Aluminum panel of diameter 1.6 meter in spiral direction. The coefficient of thermal of CFRP is very low however, a small delta temperature variation between the top and bottom sheet of CFRP of the panel will lead to panel bowing which will result in increasing power error. Hence, the objective this work is to analyse the thermal sensitivity of the 2D Profilometer. 2024 SPIE. -
Analysis on techniques used to recognize and identifying the Human emotions
Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwins work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on various recognition techniques used to identify the complexity in recognizing the facial expression is presented. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. -
ANALYSIS ON POSSIBILITIES OF SMARTPHONE USING THE COMPUTATIONAL CAPABILITY OF CLOUD
Cloud computing and mobile computing has become a big revolutionary stage in computer science communities. Both has become intertwined and facilitating end users in various fields. Cloud system administrators begin to enhance the cloud system with additional servers to help mobile devices, example is C2DM launched by Google. It is a PaaS model of cloud. It has enhanced the Smartphones limited battery power and low bandwidth using push technology. In some situations server need to push some short messages to mobile client like notification regarding new app update or event. For these kinds of features, polling or push mechanism can be used. In polling mechanism, mobile app pings server periodically and checks if any new data is available for download. Polling can make data on device stale and polling frequently can create stress on server and network. This approach is not suitable for mobile devices as it uses precious network bandwidth more and so battery consumption will be more. To overcome these Google has been introduced push technology known as C2DM which is enhancing the short comings of smart phone using the powerful computational resources of cloud. The thesis mainly concentrating on the working of C2DM, its architectural overview, life cycle overflow, enabling C2DM, sending and receiving message. Push messaging provides the possibility for mobile devices to receive messages from a content publisher via a cloud application, which is a fair example of Smartphone and cloud integration efficiency. Keywords - Intent, server ADV, client AVD, SDK, APNS, GSM, C2DM, BPS, MPNS -
Analysis on emotion-aware healthcare and Google cloud messaging
Cloud computing has the potential to get integrated with the healthcare sector. It provides functionality for managing data in a distributed environment. The concept of Healthcare services is becoming popular in the Healthcare sector as it helps the patients to get immediate access regarding his/her health related information whenever needed and wherever needed using cloud computing technology. The Big Data Application in Emotion-aware Healthcare system [BDAEH], gives attention to both the emotion factor and logical reasoning of the user. The basic functions of this system are collecting health-related data, transmitting the collected data, analyzing the received data, storing them and making it available to a user in order to perform diagnosis and predict medications. Mobile devices are becoming an essential tool in our day to day lives. By integrating the concept of Google Cloud messaging alongside BDAEH system, numerous tasks can be done efficiently. 2017 IEEE.