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GLUCOSE BOTTLE MONITORING SYSTEM USING IOT Mrs. Sasikala R[1] ,Achari Monica S [2] , Akhila N S [3] , Nishathul Aprosa S[4] ,Padma Priya S[5] [1]Assistant Professor, Department of Computer Science and Engineering,[2][3][4][5]Final Year, Department of Computer Science and Engineering,VSB College of Engineering Technical Campus, Coimbatore. ABSTRACT: Saline, one of the most popular intravenous (IV) therapy which plays a major role in the patients management who are critically ill. Surveillance of drip bottle level is very important because when the bottle is emptied and the needle is not removed from the vein then the blood flows outward into the bottle. In hospitals, the nurses or caretakers are responsible for monitoring the saline bottle level. The aim is to design an Intravenous Drip Sensor, using a capacitive probe to measure infusion rate, and display the number of drops passing through the drip chamber per minute i.e. the drip rate. If nurses working in hospitals forgot to change the glucose drip bottle once it is emptied, it will bring bad consequences to the patient .We will find the level of glucose in the glucose drip bottles that are used in the hospitals. When the glucose bottle is about to be emptied, an alert message is made to send to the nurses, doctors and attenders. The monitoring screen gets the information from observing gadgets and displays them graphically.I. INTRODUCTIONSaline level is one of the important challenges related to the management of healthcare [1]. Almost in every hospital, a nurse/caretakers is responsible to keep an eye on the saline level and if they fail to monitor this, patients suffer a lot. Drip bottle when emptied and if the needle is not removed from the patient’s vein or if the bottle is not replaced then due to the pressure difference, the blood flows outward into the bottle or the air bubbles may block the veins which may lead to serious casualty[7]. Even though there are lots of advanced devices to automate health care systems there is a serious issue to ensure the safety of the patients during IV period. So this system eliminates the need to manually monitor the level of saline water in bottle. This system uses weight sensors to determine the weight of bottle and flow sensors to determine number of drops passing through the drip chamber per minute i.e. the drip rate[8]. Therefore data collected by the sensors are sent to Arduino Uno and it processes it. SMS alert is send to caretakers using GSM(Global System for Mobile Communication) module.II. EXISTING SYSTEM Almost 80% of patients in hospitals are provided with saline water; therefore this system focuses on serious life threatening complications during intravenous therapy which is serious life threat[5]. If the drip bottles are not replaced with the new ones by time it may lead to reverse flow of blood into the drip bottles, it is known that it takes only few minutes to lose 40% of human blood which may even lead mortality[6]. So, this system made use of flexible sensors to propose a cloud computing based warning tool[4]. A remote monitoring device or mobile device is used to identify the risk level via a wireless network and cloud computing[9]. The flexible sensors are arranged in two array patterns for detection purpose. A virtual alarm unit can be employed as a early warning unit in an embedded system or tablet PC. The BHAM (Bidirectional Hetero-Associative Memory) constructs such a virtual alarm unit. III. DESCRIPTIONPROPOSED SYSTEM In recent years, there is a rapid growth in the in the field of medicine due to gradual advancements in the field of sensors, microprocessors and computers. This system is used to detect the volume of saline water in the glucose bottle by the use of weight sensors also flow sensor is used for continuous monitoring of flow rate in glucose bottle. Thus the status of the bottle will be intimated to the respective nurses or caretakers, patients attenders and the doctor. The amount of solution in the bottle can also be viewed graphically by both nurses and the attenders. This system will generate message by use of GSM module under following situations,When liquid level in glucose bottle is full, alerts as “ FULL”When liquid level in glucose bottle is reduced to 50%, alerts as “ ALERT “When liquid level in glucose bottle is reduced to 10% ,alerts as “CRITICAL”S.NO LEVEL MESSAGE1. 100% FULL2. 50% ALERT3. 10% CRITICALGlucose bottleGlucose bottle bbbbbbottleWeight Sensor & Flow sensorsflArduino boardGSMAlert message via SMS Fig.1 Basic process of proposed system IV.IMPLEMENTATIONWeight sensor Arduino UNOGSMFlow sensorFig .2. Block DiagramThis system consists of three main modulesSENSOR MODULEWeight Sensor: The weight sensor is used to get current weight or volume of the saline water in the glucose bottle. The level of liquid inside the bottle can be easy predicted. Fig . 3. Weight sensor to detect the volume Flow Sensor: It is a sensor which uses a capacitive probe to measure infusion rate, and display the number of drops passing through the drip chamber per minute i.e. the drip rate. Fig. 4. Flow Sensor to measure flow rateARDUINO UNO MODULE Arduino Uno board is a microcontroller based on ATmega328, which has 14 digital input/output pins from which it has 6 analog input pins, a USB connection, a crystal oscillator of 16 MHz and a power jack. The Arduino UNO receives data continuously from sensors.Fig .5. Arduino UNO to receive ad process dataGSM ModuleHuman can contact the system through GSM. The GSM module is used to alert the nurses, attenders of patients and the doctors through SMS which will be received with the help the SIM (Subscriber Identification Module)card.The GSM module is interfaced with the Arduino UNO for this purpose.Fig .6. GSM module for sending SMS V.CONCLUSIONThus, this system provides an efficient means to ease the work of nurses and offers more flexibility to doctors. This is mainly based on GSM technology for providing alerts describing about the three levels of liquid in the bottle besides this it enhances the care towards patients.VI. FUTURE ENHANCEMENTSThis system can be deployed on a large scale with numerous number of patients in a wing and also the same idea can be implemented to have an automatic control over the flow of glucose/drip bottle. VII.REFERENCES[1] K. Azumi, H. Shiozaki , Y. Takatuka, et al, “About the infusion solution monitor which we devised,” The Journal of Japanese Medical Instruments, vol. 44, 1974, pp. 465-467. [2] K. Iida and T. Mizuno, “A study on the dripping speed of infusion,” Bulletin of Chiba College of Health Science, 1986, pp. 55-60. [3] W. M. Caldwel A. W. Hahn l H. Maki H. Ogawa, and Y. Yonezawa, “A new drip infusion monitoring system,” Proceedings of 47th Annual Rocky Mountain Bioengineering Symposium 2010, 2010, pp. 110–116. [4] X. Wen, “Design of medical infusion monitor and protection system based on wireless communication technology,” Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application, vol. 02, 2008, pp. 755-759.[5] Y. Isamoto, G. Sugihara, D. Yamashita, O. Yamaga, et al,“Investigation about the natural fall-style infus on solution set flow quantity precision,” The Japanese Journal of Medical Instrumentation, vol.73, 2003, pp. 519-520. [6] GSM module: https://www.gsma.com/aboutus/gsm-technology/gsm.[7] P. Agrawal, T. Cordero, B. Jiang, F. Kaufman H. Neemuchwala, and A. Phukan, F. Kaufman, A. Zhong, “63-or / 63 – sugar.iq insights: An innovative personalized machine-learning model for diabetes management,” 77th Scientific Sessions, American Diabetes Association, July 2017. [8] W. He, S. Li, and , L. D. Xu “Internet of things in industries: A survey,”IEEE Transactions on Industrial Informatics, vol. 10, no. 4, pp. 2233–2243, 2014.[9] M. Hossain S. M. R. Islam, D. Kwak, M. H. Kabir, and K. sup Kwak,“The internet of things for health care: A comprehensive survey,” IEEE Access, vol. 3, 2015. [10] M. Ali, I. Ben Dhaou, T. Nguyen gia, A P. Liljeberg, and H. Tenhunen, M.A. Rahmani, T. Westerlund “An IOT-based continuous glucose monitoring system: A feasibility study,” in 8th Elsevier International Conference on Ambient Systems, Networks and Technologies, 2017, pp. 327–334.[11] M. Dürmuth and D. M. Freeman,“Deniable encryption within eligible detection probability: An interactive construction,”in EUROCRYPT, 2011, pp. 610–626. [12] D. P. 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