Vol. 1 No. 6 (2019): Volume 1, Issue 6, year 2019

Sustainable Diabetic Retinopathy Diagnosis System Using Iot

Balaramesh C
UG Student, ECE Department, DMI Engineering College, Aralvoimozhi, Kanyakumari District, Tamil Nadu, India.
Jerin L
UG Student, ECE Department, DMI Engineering College, Aralvoimozhi, Kanyakumari District, Tamil Nadu, India
Hari Krishna K
UG Student, ECE Department, DMI Engineering College, Aralvoimozhi, Kanyakumari District, Tamil Nadu, India
Shanmugam G
UG Student, ECE Department, DMI Engineering College, Aralvoimozhi, Kanyakumari District, Tamil Nadu, India
Asbin Thomas Wizar L
UG Student, ECE Department, DMI Engineering College, Aralvoimozhi, Kanyakumari District, Tamil Nadu, India.
Published November 2, 2019
  • Sustainable Computing,
  • Internet of Things,
  • Image Segmentation,
  • Diabetic Retinopathy,
  • Smart Devices
How to Cite
C, B., L, J., K, H. K., G, S., & L, A. T. W. (2019). Sustainable Diabetic Retinopathy Diagnosis System Using Iot. International Research Journal of Multidisciplinary Technovation, 1(6), 71-80. Retrieved from https://mapletreejournals.com/index.php/irjmt/article/view/264


Supportable processing gives a remote access to the finding framework for simple and quick usage. The proposed approach estimates glucose level in the blood through Dexcom G4 Platinum sensors on diabetic patients. In light of the readings, Internet of Things (IoT) stage offer a reasonable answer for Diabetic Retinopathy. The motivation behind this research is to spare the life of the patient from vision misfortune. The procedure begins from the gadgets themselves which safely move data with IoT stage and vow the regular language for the portable applications to work together with one another. This stage always accumulates a huge number of data from the gadget and store in a protected database. It fuses the information got from IoT gadgets and applies investigation to anticipate significant information to address clinical needs. The outcomes shown by the execution of the proposed methodologies are practically identical with the modern frameworks in relations of exactness, particularity and affectability. The proposed method performs superior to different systems by accomplishing a normal 99.58% Precision, 72.51% Sensitivity and 99.83% Specificity in the trial arrangement.


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