Created August 6, 2020 © GPL3+

Smart Hospital

A smart hospital where medical staff can remotely monitor patients without going near them

IntermediateShowcase (no instructions)Over 1 day574

Things used in this project

Hardware components

Nordic Semiconductor nRF52 Development Kit

SG90 Micro-servo motor

Espressif ESP8266 ESP-12E

LED (generic)

Raspberry Pi Camera Module

Espressif ESP32S

Software apps and online services

Node-RED

Exitum Espressif IDE

Arduino IDE

Keil Studio

Story

Problem

The coronavirus pandemic has brought the world to its knees. The only reason is the highly contagious nature of the virus. Healthcare systems worldwide are not competent enough to deal with this due to several reasons like- - Lack of equipment - Lack of doctors - Lack of protective equipment Our last line of defence - the doctors, put in every effort to treat their patients. However, more often than not they contract this deadly disease in the bargain. Their exists no method to directly treat patients without coming in contact with them even for the treatment of coronavirus, which is not very complicated except in extreme cases. The key interactions of the medical staff with the patients include - - Cleaning of wards - Giving food and medicines - Body temperature monitoring - Collecting blood samples - Giving instructions - Essential equipment monitoring While solutions to the first two problems exist already as hospitals at many places have incorporated ground robots for this task. Taking temperature samples can easily be done by medical staff from a safe distance and there is no scope for innovation on that front. No viable solutions exist for the other three problems, which is why everyday hundreds of doctors are getting affected. In areas where the number of doctors is less, this is a really serious issue. Due to the multitudes of patients turning up at hospitals, doctors are being forced to work overtime which is extremely stressful for them. Cases of suicide by such doctors have been reported.

Solution

I propose a connected hospital consisting of nodes in the form of patient beds that are able to log and control essential equipment data, collect blood samples, monitor patient health and raise alarms when necessary. The beds would form a BLE mesh network and connect to a central LoRa station that would send notifications to medical staff across a network of connected wards in various hospitals. The beds would be equipped with microphones and speakers for the doctor-patient interaction. They would have a panel of buttons for the patients to ask for certain essentials like food or water. The panel would also include a button for summoning hospital staff in case of an emergency. There would be a provision for the monitoring essential devices like the ventilator, the ECG, the EKG etc. The data from all these devices would be sent to the central station where it would be analysed and if a problem arises the central system publishes the anomaly along with the patient number through a gateway to the Helium network. Once online, the data is used by a web service to send important notifications to the doctor incharge. The doctor may then take preventive measures autonomously by changing settings on the life-support devices. If the assigned doctor is not available, the web service automatically sends notifications to doctors connected to the network who can then volunteer and take life-saving decisions, everything autonomously. This might sound far-fetched but the impact such a system can have is enormous. A web application would enable the doctors full control over life-support devices of the patient. The data can be collected on demand and collected for medical research. For developed hospitals with a WiFi connection, the patient logs can be directly stored on a central database which can be used later. For hospitals in underdeveloped areas this data may be stored on an SD card and then checked from time to time by hospital staff manually. The beds would also have a provision for the attachment of a non-intrusive sample collector and drug injector that has to be installed manually but can be operated remotely by means of robotic arms controlled by servo motors. This would definitely improve the condition of medical staff, keeping them safe, reducing their workload, allowing real-time monitoring, allowing control of life support devices remotely and saving many unnecessarily lost lives by taking quick decisions remotely.

Working

I would make nodes based on the NRF52832 boards which support BLE. The node would have connectors for inputs from various life-support devices. A robotic arm with 6DOF from a previous project would serve for control of sample collector devices. The central LoRa station would be made from the Helium Developement kit and would communicate with the nodes with an NRF52832 board. Patient logs are stored in an SD card interfaced with the Helium Dev kit. The sensor shield accompanying the kit would serve as a temperature and humidity controller and would open and close windows automatically. The data sent to the central station would be monitored and analysed based on predefined parameters on a per patient basis. If an anomaly is found, the concerned medical staff is immediately informed and the doctor takes control of life-support equipment. If any instruction is to be given, the doctor speaks to the patient through a speaker on the bed. The sounds can be recorded beforehand and programmed onto the JQV-500 audio board using over the air(OTA) update feature of the NRF boards. The recording can be played at a time as determined by the doctor allowing interaction without actually going close to the patient. The patient can key in certain instructions to the hospital staff with the help of a panel of buttons with pre-defined functions. An alert button is also present for the patient to call out for help. These functions would be implemented as interrupts in the control station code. If an injection is to be given or a sample is to be collected, hospital staff would fix the device on the robotic arm. It would then be controlled by the doctor remotely by means of the app which connects to the web service. The webservice is made on NodeRed and acts as a link between the central station and the doctors. The doctors are able to interact with the network with the help of an app made on the MIT App Inventor. It provides a panel for monitoring of patients and to control the sample collector and other life-support devices. It also has the option to record audio to send to the patient. The webservice also sends notifications directly to doctors and other medical staff which can be received on the app. If the assigned doctor is not available, the web service automatically sends notifications to doctors connected to the network who can then volunteer and take life-saving decisions, everything autonomously.

Benefits and Conclusion

With the Helium network soon to be deployed to many countries, I would be able to scale the product to create a huge network of connected hospital wards that can send critical patient monitoring data to the cloud. The data can then be used to monitor and control life-support devices remotely and also be used for medical research. It connects the patients to a network of doctors who can voluntarily perform treatment without coming in contact with patients, improving their work conditions and saving them from unnecessary stress

The chief benefits the concept has are- - Improved quality of life for doctors - Medical staff would need to come in minimal contact with infected wards - Remote and timely treatment - Life-saving treatment can be done remotely - Availability of patient data for medical research - Reduced stress and work-time for medical staff

Helium Network Ping

#include "LoRaWAN.h"

const char *devEui = "FILL_ME_IN";
const char *appEui = "FILL_ME_IN";
const char *appKey = "FILL_ME_IN";

// Max Payload 53 Bytes for DR 1
const uint8_t payload[] = "Hello, World!";

void setup( void )
{
    Serial.begin(9600);
    
    while (!Serial) { }

    // US Region
    LoRaWAN.begin(US915);
    // Helium SubBand
    LoRaWAN.setSubBand(2);
    // Disable Adaptive Data Rate
    LoRaWAN.setADR(false);
    // Set Data Rate 1 - Max Payload 53 Bytes
    LoRaWAN.setDataRate(1);
    // Device IDs and Key
    LoRaWAN.joinOTAA(appEui, appKey, devEui);

    Serial.println("JOIN( )");
}

void loop( void )
{
    if (LoRaWAN.joined() && !LoRaWAN.busy())
    {
        Serial.print("TRANSMIT( ");
        Serial.print("TimeOnAir: ");
        Serial.print(LoRaWAN.getTimeOnAir());
        Serial.print(", NextTxTime: ");
        Serial.print(LoRaWAN.getNextTxTime());
        Serial.print(", MaxPayloadSize: ");
        Serial.print(LoRaWAN.getMaxPayloadSize());
        Serial.print(", DR: ");
        Serial.print(LoRaWAN.getDataRate());
        Serial.print(", TxPower: ");
        Serial.print(LoRaWAN.getTxPower(), 1);
        Serial.print("dbm, UpLinkCounter: ");
        Serial.print(LoRaWAN.getUpLinkCounter());
        Serial.print(", DownLinkCounter: ");
        Serial.print(LoRaWAN.getDownLinkCounter());
        Serial.println(" )");

        // Send Packet
        LoRaWAN.sendPacket(1, payload, sizeof(payload));
    }

    delay(20000); //20 Seconds
}

Credits

Moinak Ghosh

11 projects • 38 followers

IoT enthusiast experienced with autonomous drones and vehicles, FPGA-based vision applications, MCU programming/Embedded/ML/AI

Smart Hospital

Things used in this project

Hardware components

Software apps and online services

Story

Problem

Solution

Working

Benefits and Conclusion

Code

Helium Network Ping

Credits

Moinak Ghosh

Comments

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Smart Hospital

Smart Hospital

Things used in this project

Hardware components

Software apps and online services

Story

Problem

Solution

Working

Benefits and Conclusion

Code

Helium Network Ping

Credits

Moinak Ghosh

Comments

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