A Fuzzy-Ontology Based Diabetes
Monitoring System Using Internet
of Things
Sondes Titi
1,2(B) , Hadda Ben Elhadj
1,2 , and Lamia Chaari Fourati
1,2
1 Laboratory of Technology and Smart Systems (LT2S), LR16CRNS01, Sfax, Tunisia
contact@crns.rnrt.tn
2 Digital Research Center of Sfax, Sfax, Tunisia
Abstract. The majority of the Internet-of-things (IoT)-based health
monitoring systems adopt ontologies to represent and interoperate the
huge quantity of data collected. Classical ontologies cannot appropriately treat imprecise and ambiguous knowledge. The integration of Fuzzy
logic theory with ontology can effectively resolve knowledge problems
with uncertainty. It considerably raises the accuracy and the precision
of healthcare decisions. This paper presents a fuzzy-ontology based system using the internet of things and aims to ensure continues monitoring
of diabetic patients. It mainly describes the ontology-based model and
the semantic fuzzy decision-making mechanism. The system is evaluated
using semantic querying. The results indicate its feasibility for effective
remote continuous monitoring for diabetes.
Keywords: Fuzzy · Ontology · Internet of thing · Healthcare ·
Diabetes
1 Introduction
The increasing number of diabetic patients place a severe burden on healthcare
systems and makes their monitoring a very difficult task. According to [17], the
total number of diabetic patients is expected to rise from 171 million in 2000 to
366 million in 2030. Diabetes is a group of metabolic disorders of carbohydrate
metabolism characterized by the variation of blood glucose level that results from
insufficient production of the hormone insulin (type 1 diabetes) or an ineffective response of cells to insulin (type 2 diabetes). It requires remote continuous
monitoring to prevent emergencies and long-term complications such as cardiovascular diseases. Therefore, its treatment should focus mainly on controlling and
managing blood glucose levels constantly with diet, physical exercises, and medications. New healthcare systems based on IoT offer a new effective perspective
in diabetes management based on the IoT data collected. They are enable to sufficiently handle imprecise and vague information related to patient and therefore
fail in describing his health condition and to recommend the appropriate drug
c
The Author(s) 2020
M. Jmaiel et al. (Eds.): ICOST 2020, LNCS 12157, pp. 287–295, 2020.
https://doi.org/10.1007/978-3-030-51517-1_25
Monitoring System Using Internet
of Things
Sondes Titi
1,2(B) , Hadda Ben Elhadj
1,2 , and Lamia Chaari Fourati
1,2
1 Laboratory of Technology and Smart Systems (LT2S), LR16CRNS01, Sfax, Tunisia
contact@crns.rnrt.tn
2 Digital Research Center of Sfax, Sfax, Tunisia
Abstract. The majority of the Internet-of-things (IoT)-based health
monitoring systems adopt ontologies to represent and interoperate the
huge quantity of data collected. Classical ontologies cannot appropriately treat imprecise and ambiguous knowledge. The integration of Fuzzy
logic theory with ontology can effectively resolve knowledge problems
with uncertainty. It considerably raises the accuracy and the precision
of healthcare decisions. This paper presents a fuzzy-ontology based system using the internet of things and aims to ensure continues monitoring
of diabetic patients. It mainly describes the ontology-based model and
the semantic fuzzy decision-making mechanism. The system is evaluated
using semantic querying. The results indicate its feasibility for effective
remote continuous monitoring for diabetes.
Keywords: Fuzzy · Ontology · Internet of thing · Healthcare ·
Diabetes
1 Introduction
The increasing number of diabetic patients place a severe burden on healthcare
systems and makes their monitoring a very difficult task. According to [17], the
total number of diabetic patients is expected to rise from 171 million in 2000 to
366 million in 2030. Diabetes is a group of metabolic disorders of carbohydrate
metabolism characterized by the variation of blood glucose level that results from
insufficient production of the hormone insulin (type 1 diabetes) or an ineffective response of cells to insulin (type 2 diabetes). It requires remote continuous
monitoring to prevent emergencies and long-term complications such as cardiovascular diseases. Therefore, its treatment should focus mainly on controlling and
managing blood glucose levels constantly with diet, physical exercises, and medications. New healthcare systems based on IoT offer a new effective perspective
in diabetes management based on the IoT data collected. They are enable to sufficiently handle imprecise and vague information related to patient and therefore
fail in describing his health condition and to recommend the appropriate drug
c
The Author(s) 2020
M. Jmaiel et al. (Eds.): ICOST 2020, LNCS 12157, pp. 287–295, 2020.
https://doi.org/10.1007/978-3-030-51517-1_25