An Internet-of-Things (IoT) Network System for Connected Safety and Health Monitoring Applications
Abstract
:1. Introduction
2. Related Works
2.1. Wireless Technologies
2.2. IoT Gateway
2.3. Monitoring Applications
3. System Architecture
3.1. Wearable Network
3.2. IoT Gateway
3.3. IoT Cloud
3.4. Network Implementation
4. Implementation of the Sensor Node
4.1. Safe Node
4.1.1. Power Management Unit
4.1.2. Environmental Sensors
4.1.3. MCU and Wireless Transmission
4.1.4. Software Implementation for Safe Node
4.2. Health Node
4.2.1. Signal Processing Board
4.2.2. Physiological Sensors
4.2.3. Software Implementation
5. System Performance Evaluation and Analysis
5.1. Network Coverage
- Firstly, the IoT gateway is placed close to the window inside the laboratory on the second floor. Then we move the gateway to the top of the building to test the network coverage range when the gateway is at different gateway locations.
- Each sensor node is configured to send the data to the IoT gateway every minute.
- LoRa configuration: (1) Transmission power: 23 dBm; (2) Frequency: 915 MHz; (3) Spreading Factor = 128 chips/symbol (SpreadingFactor (SF) = 7); (4) BW = 125 kHz; (5) CR = 4/5.
5.2. Sensors’ Performance
6. Implementation of the IoT Gateway and Cloud Server
6.1. IoT Gateway Implementation
6.1.1. Hardware Implementation
- Internet connection interface, such as Wi-Fi or Ethernet;
- Relatively high processing speed;
- Data storage unit, such as MySQL database;
- User-friendly interface.
- One USB port of Pi is used to connect the LoRa, which enables the data acquisition from the local sensor network to the gateway database.
- MySQL database is installed in the Raspbian system for data storage. The data can be accessed in future if required.
- The built-in Wi-Fi module is used for Internet connection.
- MQTT messaging protocol is installed in the system for transmitting the data to the cloud server.
- A light-weight web server based on Node.js is installed and can be accessed via a smartphone and web browsers.
6.1.2. Software Implementation
6.2. IoT Cloud Server
7. Conclusions and Future Works
Author Contributions
Funding
Conflicts of Interest
References
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Parameters | Model | Main Specifications | Power |
---|---|---|---|
MCU | Simblee | 32-bit ARM Cortex-M0 16 MHz, 29 GPIOs | Operating voltage: 1.8–3.6 V <600 nA in sleep mode |
BLE | Simblee | −93 dBm receiver sensitivity | 8 mA TX @ 0 dBm 10 mA Rx |
LoRa | RFM95 | −148 dBm receiver sensitivity | 20–120 mA TX 10 mA RX, 0.2 µA Sleep |
LDO | MCP1810 | Input voltage: 3.6–5.5 V | 20 nA quiescent current 1 nA @ sleep |
Switch | TPS22098 | Input voltage: 1–3.6 V | 1 µA quiescent current 1 µA @ sleep |
Temperature | BME680 | −40–+85 °C | 0.15 µA @sleep 2.1 µA measuring |
Relative humidity | BME680 | 0–100% RH | same as above |
CO2 | COZIR-GC0012 | 0–10,000 ppm | 1.5 mA @ 3.3 V |
UV | SI1145 | 1–11+ Index | 500 nA Sleep, 9 µA average |
Parameters | Model | Main Specifications | Power |
---|---|---|---|
MCU | Simblee | 32-bit ARM Cortex-M0 16 MHz, 29 GPIOs | Operating voltage: 1.8–3.6 V <600 nA in sleep mode |
BLE | Simblee | −93 dBm receiver sensitivity | 8 mA TX @ 0 dBm 10 mA Rx |
Buck-boost converter | RT6150A/B | Input & output voltage: 1.8–5.5 V | <1 µA shutdown current |
Charging controller | MCP73831 | fast charging mode constant voltage charging mode | Charging current: 15 mA–500 mA |
Body temperature | MAX30205 | 0.1 °C (37 to 39 °C) | Operating voltage: 2.7–3.3 V Supply current: 600 µA |
PPG | LED: AM2520ZGC09 PD: APDS9008 | Peak wavelength: 525 nm Peak sensitive wavelength: 565 nm | LED voltage: 1.6–5.5 V PD supply current: 42 µA |
Sensor | Data | Alerts and Action |
---|---|---|
Temperature | >30 | remind the subject to rest and drink more water |
UV | >5 | remind the subject to rest and avoid working under direct sunlight |
CO2 | >800 | notify the subject to avoid working for too long in a poor air condition environment |
Heart rate | >140 | notify subject to rest |
Body temperature | >35 | notify subject to rest |
Parameters | [32] | [35] | [36] | [53] | This Work |
---|---|---|---|---|---|
MCU | - | Cortex-M3 | CC2540 | CC2541 | Cortex-M0 |
Wireless technologies | BLE | 6LoWPAN RFID | BLE | BLE | BLE and LoRa |
Range | Short | Short | Short | Short | Short to Long |
Physiological parameters | ECG, respiration, heart rate, body temperature, blood oxygen | Motion, ECG | PPG, hydration | PPG, motion, Skin impedance, ECG, VOC, ozone, respiratory rate | Body temperature, heart rate |
Environmental parameters | temperature, humidity, noise, air quality | Temperature, barometric pressure, ambient light | pressure, gas, VOC | Ambient temperature, relative humidity | Ambient temperature, relative humidity, UV, CO2 |
IoT realization | Yes | Yes | - | - | Yes |
Sensor node location | Cloth | - | Wrist | Chest, wrist, handhold | Top of helmet, chest |
Power requirements | Rechargeable battery | 3-V rechargeable battery | Solar with 20 mAh rechargeable battery | Rechargeable battery | 3.6-V rechargeable battery |
Application | Healthcare | Healthcare system for hospital | Healthcare | Healthcare for Chronic Respiratory Disease | Safety and health monitoring for industrial workplace |
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Wu, F.; Wu, T.; Yuce, M.R. An Internet-of-Things (IoT) Network System for Connected Safety and Health Monitoring Applications. Sensors 2019, 19, 21. https://doi.org/10.3390/s19010021
Wu F, Wu T, Yuce MR. An Internet-of-Things (IoT) Network System for Connected Safety and Health Monitoring Applications. Sensors. 2019; 19(1):21. https://doi.org/10.3390/s19010021
Chicago/Turabian StyleWu, Fan, Taiyang Wu, and Mehmet Rasit Yuce. 2019. "An Internet-of-Things (IoT) Network System for Connected Safety and Health Monitoring Applications" Sensors 19, no. 1: 21. https://doi.org/10.3390/s19010021
APA StyleWu, F., Wu, T., & Yuce, M. R. (2019). An Internet-of-Things (IoT) Network System for Connected Safety and Health Monitoring Applications. Sensors, 19(1), 21. https://doi.org/10.3390/s19010021