Automatic Tablet Dispenser for Patients with Health Monitoring System

International Research Journal of Engineering and Technology (IRJET) e ISSN:2395 0056

Automatic Tablet Dispenser for Patients with Health Monitoring System

Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India ***

Abstract The main theme of this paper is to automate the tablet dispensing process for older and sick patients who can easily forget their medicine intake or mistakenly take the wrong medicine at the wrong time. This project will ensure the tablet dispensing process is carried out at the right time whenever it is required and the right tablet is dispensed to the patients with correct dosage. Additionally the health monitoring system by increasing the scalability with the power of the internet of things.

Key Words: Internet Of Things,

1. INTRODUCTION TO AUTOMATIC MEDICINE DISPENSER

AnautomaticmedicinedispenserisusedusuallyintheareawheretheAlzheimerpatientsneedassistance.Inthiskindof system the medicine will be automatically dispensed based on the prescribed or preprogrammed interval of time. This systemofmedicinedispenserwillbemorehelpfulforelderpersonsandthepersonswithdifferentdisabilities.Themain threatinautomaticmedicinedispenseristhatthemedicinewillbedispensedonlybasedonthepreprogrammedinterval oftimewithoutbeinganalyzingthecurrenthealthconditionofthepatientthemedicinewillbedispensed.Thisformsthe majorthreatforthemedicineconsumingpersonsendangeringtheirlifewhenthepatientisinreallycriticalconditionand requiresthedifferentmedication,butthemedicinedispensewillonlydispensetheregularroutinemedicinethattoointhe predefinedintervaloftime.

1.1 EXISTING SYSTEM

In the existing system, the pill dispenser is made available for dementia patients and hence the pill will be dispensed automatically for the patients in the predefined time. In this system of process, there lies the high risk in medical error sincethemedicinewillbedispensedbasedontheregularintervaloftime.Inthisscenario,thepatienthealthconditionis notmonitoredandthemedicinebasedonthepatienthealthconditionisnotimplemented.

1.2 PROPOSED SYSTEM

IntheproposedsystemIntegrationofwirelesssensortomeasurethepatienthealthperiodically/continuouslyandsend the data to cloud is performed. By using machine learning technique, the commands are sent to the robotic vehicle. The outputofthesensoriscommunicatedtothecontrolleroftherobotandiscomparedwiththestandardhealthvalues,ifis abnormal then the robot provides medicine to the patient. The patient medication details can also be communicated to familymember/doctorwhenitrequiredemergency.Roboticarmisusedtoservethepills.

2.1BLOCK DIAGRAM

In our project we have used NODE MCU which is the evolved IoT development board from the raw ESP8266 WIFI core chip.InthismoduletheprogrammingofESP8266ismadepossiblewithoutanyadditionalexternalcomponents.Ithasin buildUSBtoSeriallycontrollerCH340GwhichsupportstoretrievedatafromESP8266seriallyandhenceitformseasyto viewthedatathusobtainedfromsensors.ThepowersupplytotheNODEMCUcanbepoweredexternallythroughVINand GNDpinorthroughtheUNIVERSALUSBpin.

The sensors like PULSE sensor and temperature sensor is connected to the NODE MCU GPIO pin and ADC pins respectively.Thedataachievedfromthepulsesensorisdigitaldataandhencethusobtaineddatacanreadbythedigital pinitself.Thepulsesensorconsistsofoneopticaltransmitterandoneopticalreceiverin whichthepatientfingeriskept. Oncethepatientkeepsthefingerinthesensor,basedonthebloodstreamthatpassesthroughthefinger,thepulsesensor gives the pulsated output which is further processed by the NODE MCU and pulse obtained from the patient body is calculatedanddisplayedasapulse/min.

Volume: 09 Issue: 05 | May 2022 www.irjet.net p ISSN:2395 0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 3450

International Research Journal of Engineering and Technology (IRJET) e ISSN:2395 0056

ThetemperaturesensorLM35isconnectedtotheA0pinofNODEMCUwhichistheonlyoneanalogpinavailable in the NODE MCU. The temperature sensor used here in our project is capable of monitoring the temperature from 55 degree centigrade to 150 degree centigrade. Additionally the main choice of us to choose this type of sensor is it draws only 60 microampere for its operation and hence it produces very less heat dissipation. Finally thus obtained data from heartbeat sensor and temperature sensor is transferred to the THINKSPEAK cloud platform with the help of NODE MCU throughthepreconfiguredSSIDandPASSWORD.THINKSPEAKserverwehavechoseninourprojectmainlybecauseofits reliability,scalabilityanditisanopensourceplatformthatcanbeaccessedfromanywhereintheworld.

Figure 1: DataAcquisition

Figure 2: MachineusingKNN

The second stage of our project is decision making process. Since the sensor data is made available in the cloud platform,itcanbemonitored,manipulatedandvisualizedthroughthegraphicalrepresentationwithlivetimestamp.The machine learning algorithm is used in our project to classify and make decision when the patient has to treat with the appropriatetabletbasedontheirhealthconditionandthedataistransferredtotheroboticarmvehicle.

The third stage of our project is nothing but data retrieving from cloud storage with the help of NODE MCU and hencewiththehelpofacquireddatafromthecloudplatform,desireddecisionoftabletdispensingismadepossible.Once thedecisionisfinallymade,theservomotorsthathasbeenconnectedtothePWMpinsofNODEMCUunitisactivatedto dispensethetablet.

Volume: 09 Issue: 05 | May 2022 www.irjet.net p ISSN:2395 0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal |

International Research Journal of Engineering and Technology (IRJET) e ISSN:2395 0056

Volume: 09 Issue: 05 | May 2022 www.irjet.net p ISSN:2395 0072

2.2 DESIGN METHODOLOGY

Figure 3: RoboticARMControlSystem

Figure 4: CircuitDiagram

The above design describes the entire circuit diagram of this project “Automatic Tablet Dispenser for Patients with Health Monitoring System”. As shown in the above figure, the circuit diagram is classified into transmission and receptionside.Inthetransmissionside,thetemperaturesensorandthepulsesensorisconnectedtotheNODEMCUand hence the data acquired from the sensor is sent to the cloud platform. And hence from the reception side thus acquired datafromthecloudplatformisdecodedandbasedonthedecisionmadebythemachinelearningalgorithminPythonthe appropriatetabletisdispensedtothepatientwiththehelpofthreeservomotorsusedtocontroltheroboticarm.TheH BridgemotordriverisusedinthisprojectinordertomovetheroboticARMvehiclefromoneplacetoanother.H Bridge driverismadewiththehelpofL293DmotordriverwhichcanbeabletorotatethegearedDCmotoroftheroboticvehicle clockwiseandanti clockwisebasedontheinputpulsegiventothemotordriver.Oneoftheuniquefeatureofthisdriveris breakingoperation.Oncetheinputterminalofthemotorterminalisidlei.e 0,0or1,1thebreakingpulseisappliedtothe motorpreventingtherobotfromslidingevenintheslantingsurface.

International Research Journal of Engineering and Technology (IRJET) e ISSN:2395 0056

Volume: 09 Issue: 05 | May 2022 www.irjet.net p ISSN:2395 0072

FLOW CHART

Figure 5: FlowChart

Asshownintheabovefigurethesystemgetsinitializedanditisdescribedinthestart block.Thediamondblock followedbythestartblockisusedtocheckvitalparametersofthepatientandoncethedataacquiredthusacquireddatais senttothecloudserver.Ifthedataisnotacquired,thesystemwillwaitforthedatauntilthedata receives.Thusthedata made available in the cloud server is retrieved and processed through machine learning algorithm and the result is processed which is represented by the diamond box. If the result is normal, the overall process comes to end and it is represented by the end terminal block. Once the result is found to be abnormal, the signal is sent to the robot and it is represented by the process box of flowchart, further robot will provide appropriate medicine to the patient and the processisfinallyterminated.

2.4

International Research Journal of Engineering and Technology (IRJET) e ISSN:2395 0056

Volume: 09 Issue: 05 | May 2022 www.irjet.net p ISSN:2395 0072

SIMULATION RESULTS

Figure 6: SimulationResult1 Figure 7: SimulationResult2

Theabovefigure(fig6)representstheoutputdata of thesensorfromthepatientbodywhichhasbeendisplayedinthe livewebserver. Theabove figure(fig7)representslivetemperaturedataloggedtothewebserverwhichisshowingthe temperaturevalueas28degreeCelsiusandalongwiththatdatadateandtimeisdisplayedinthewebserver.

Figure 8: SimulationResult3

The above figure represents live heartbeat data logged to the web server which is showing the heartbeat value above15alongwiththatdatadateandtimeisdisplayedinthewebserver.

3. CONCLUSIONS

Thus by the help of our project, the patient vital parameter like heartbeat and temperature is continually monitored in the cloud platform and hence the patient health is analyzed through KNN machine learning algorithm and overall tablet dispensingprocessfortheneedypatientisfullyautomatedandthedesiredtabletisdispensedtothepatientwheneverit isrequired bythe patientautomaticallywiththehelpofroboticarm. Thissystemalsopreventsthemanual tableterrors sinceentireprocessiscarriedoutbythepredefinedsetofinstructions..

© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 3454

International Research Journal of Engineering and Technology (IRJET) e ISSN:2395 0056

Volume: 09 Issue: 05 | May 2022 www.irjet.net p ISSN:2395 0072

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© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 3455