Breast Lump Assessment: An IoT-Integrated Framework with Advanced Localization Techniques

Authors

  • M Kavitha Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Author
  • Singaraju Srinivasulu Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Author
  • P S Latha Kalyampudi Department of Computer Science, Central Tribal University of Andhra Pradesh, Kondakarakam Village, Vizianagaram, Andhra Pradesh-535003 Author
  • N. Sunanda Department of CSE-(CyS,DS) and AI&DS, VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad, 500090 Author
  • M Kalyani Department of Information Technology, PACE Institute of Technology & Sciences, ongole, India. Author
  • V Gopikrishna Department of Information Technology, MLRIT. Dundigal, Hyderabad. Author
  • D Mythrayee Department of Information Technology, MLRIT, Dundigal ,Hyderabad Author

DOI:

https://doi.org/10.56294/dm2025849

Keywords:

Breast Lumps, Internet of Things, Lump, Sensor, Wearable Jacket

Abstract

Internet of Things (IoT) influences many areas such as healthcare, transportation, agriculture, industry control, environment monitoring, and water management. Healthcare is a major area in which the IoT enables a more personalized form of healthcare through smart healthcare systems. Breast cancer is the second leading cause of death among women globally, and its incidence is increasing every year. Early-stage detection of breast cancer is an important research challenge in the medical field. The aim of this article is to design an IoT - Integrated framework with advanced localization techniques for breast lump assessment. Through the proposed framework, breast lumps are monitored periodically using sensor embedded wearable jacket. The lump position and its depth in the breast are evaluated using localization techniques in sensor organization. Model outcome is analysed for six periodic tests data. Results evidence that periodic monitoring of breast health using the designed framework is effective to fix abnormal lumps at the early stage.

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Published

2025-04-16

Issue

Section

Original

How to Cite

1.
Kavitha M, Srinivasulu S, Latha Kalyampudi PS, Sunanda N, Kalyani M, Gopikrishna V, et al. Breast Lump Assessment: An IoT-Integrated Framework with Advanced Localization Techniques. Data and Metadata [Internet]. 2025 Apr. 16 [cited 2025 May 23];4:849. Available from: https://dm.ageditor.ar/index.php/dm/article/view/849