Abstract
Thousands of gigabytes of data mostly are now available on the internet, for all intents and purposes gathered from a variety of sources, deliberately or inadvertently. The science of converting all of this data into knowledge that can specifically improve everyone’s life pretty much simpler definitely is known as Big Data. Today, healthcare literally is one of the most important sectors. Our country’s healthcare resources basically are minimal, which particularly is fairly significant. As a result, making resources available to everyone in need becomes extremely difficult in a generally major way. Big Data Analytics can assist us in optimising the usage of these resources so that they particularly are available to anybody who requires them, which basically is quite significant. Keeping track of the resources that kind of are currently in use, those that literally are available, and those that may for all intents and purposes be reassigned is one strategy to optimise the available resources in a subtle way. These systems help us in determining the actually exact location of all resources definitely such that the ones nearest to the patient basically are allocated to him, making the treatment process faster. Indoor positioning systems definitely are like GPS systems but that work inside a building, in this case, hospital, which is fairly significant. This chapter discusses further about the contribution of big data analytics and indoor positioning systems in the evolution of smart healthcare.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Nambiar AR, Reddy N, Dutta D (2017) Connected health: opportunities and challenges. In: IEEE international conference on big data, IEEE, Boston, MA, pp 1658–1662
Mishra S, Mahanty C, Dash S, Mishra BK (2019) Implementation of BFS-NB hybrid model in intrusion detection system. In: Recent developments in machine learning and data analytics, Springer, Singapore, pp 167–175
Dwivedi S, Kasliwal P Soni S (2016) Comprehensive study of data analytics tools (RapidMiner, Weka, R tool, Knime). IEEE symposium on Colossal Data Analysis and Networking (CDAN), Indore
Zhuhadar LP, Thrasher E (2019) Data analytics and its advantages for addressing the complexity of healthcare: a simulated zika case study example. Appl Sci 9:2208
Dimitrov DV (2016) Medical internet of things and big data in healthcare. Healthc Inf Res 22(3):156–163
Johri P, Singh T, Das S, Anand S (2017) Vitality of big data analytics in healthcare department. In: IEEE international conference on infocom technologies and unmanned systems (trends and future directions), Dubai
Wang H, Zhang Q, Ip M, Lau JTF (2018) Social media–based conversational agents for health management and interventions. Comput 51:26–33
Agha L (2015) The effects of health information technology on the costs and quality of medical care. J Health Econ 34:19–30
Burke J (2015) Is that data valid? Getting accurate financial data in healthcare. Health Catalyst
Diao J, Kohane IS, Manrai AK (2018) Biomedical informatics and machine learning for clinical genomics. Hum Mol Genet 27:R29–R34
Uddin MS, Alam JB, Banu S (2017) Real time patient monitoring system based on internet of things. In: 4th IEEE international conference on advances in electrical engineering, Dhaka
Olaronke I, Oluwaseun O (2016) Big data in healthcare: prospects, challenges and resolutions. In: Future technologies conference, IEEE, San Francisco, CA, pp 1152–1157
Gawanmeh A (2016) Open issues in reliability, safety, and efficiency of connected health. In: First IEEE conference on connected health: applications, systems and engineering technologies, Washington, DC
Sonune S, Kalbande D, Yeole A, Oak S (2017) Issues in IoT healthcare platforms: a critical study and review. In: IEEE international conference on intelligent computing and control (I2C2), Coimbatore
Williams C, Mostashari F, Mertz K, Hogin E, Atwal P (2012) From the office of the national coordinator: the strategy for advancing the exchange of health information. Health Aff 31(3):527–536
Mishra S, Sahoo S, Mishra BK (2019) Addressing security issues and standards in Internet of things. In: Emerging trends and applications in cognitive computing, IGI Global, pp 224–257
Thakkar H, Mishra S, Chakrabarty A (2012) A power efficient cluster-based data aggregation protocol for WSN (MHML). Int J Eng Innov Technol (IJEIT) 1(4):241–246
Rath M, Mishra S (2020) Security approaches in machine learning for satellite communication. In: Machine learning and data mining in aerospace technology, Springer, Cham, pp 189–204
Mishra S, Tripathy HK, Panda AR (2018) An improved and adaptive attribute selection technique to optimize dengue fever prediction. Int J Eng Technol 7:480–486
Mishra S, Tadesse Y, Dash A, Jena L, Ranjan P (2021) Thyroid disorder analysis using random forest classifier. In: Intelligent and cloud computing, Springer, Singapore, pp 385–390
Rath M, Mishra S (2019) Advanced-level security in network and real-time applications using machine learning approaches. In: Machine learning and cognitive science applications in cyber security, IGI Global, pp 84–104
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Patnaik, M., Mishra, S. (2022). Indoor Positioning System Assisted Big Data Analytics in Smart Healthcare. In: Mishra, S., González-Briones, A., Bhoi, A.K., Mallick, P.K., Corchado, J.M. (eds) Connected e-Health. Studies in Computational Intelligence, vol 1021. Springer, Cham. https://doi.org/10.1007/978-3-030-97929-4_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-97929-4_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-97928-7
Online ISBN: 978-3-030-97929-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)