Smart Wearable Sensor System for IOT Connected Safety and Health Applications

1. Smart Wearable Sensor System for IOT-Connected
Safety and Health Applications.
Fathima.S
CHN16EC040
College of Engineering Chengannur
Department of Electronics and Communications Engineering
August 26, 2019
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2. Overview
1 Objective
2 Internet of Things, a promising technological paradigm.
3 Existing technologies
4 The WBAN system
5 The Architecture
6 Implementation
7 Future Scope
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3. Objective
Key objective
To present a wearable sensor network system for Internet of Things (IOT)
connected safety and health applications
Safety and health of workers are important for industrial workplace.
Outdoor environments such as UV, ozone, CO are harmful to human
health.
Indoor air pollutants CO2, smoke, CO, and VOC.
Physiological parameters like body temperature and heart rate.
There arises a need for an effective network system to improve the
safety in workplaces.
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4. Introduction
Internet of Things, a promising technological paradigm.
’Things’ connected to Internet are projected to cross 50 billion by 2020
and 100 billion by 2030.
IOT is influencing our lifestyle from the way we react to the way we
behave.
IOT is a giant network of connected devices and is all by using
sensors.
Unification of technologies such as low-power embedded system,big
data,cloud computing,machine learning and networking.
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5. Existing technologies
Wearable Body area Network(WBAN) to monitor physiological
signals[2].
Wrist worn wearable system for photoplethysmogram(PPG)
monitoring.[2]
A WBAN with motion and electrocardiogram(ECG) sensors for
rehabilitation[3].
Edge-based WBAN for heart rate monitoring[4].
Wearable sensor network for indoor environmental monotoring[7].
Works continuously monitoring the environment and health of the
subjects for chronic respiratory diseases.[8] .
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6. The WBAN system
A heterogeneous wearable IOT sensor network system for connected
safety and heath applications.
Multiple sensor nodes.
Safe Node
Environmental condition monitoring including ambient temperature,
relative humidity, UV and CO2[6]
Health Node
Physiological signals monitoring including body temperature and heart
rate.
Two wireless technologies
BLE for short range data transmission
LoRa for long range data transmission.
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7. The Architecture
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8. Hardware Implementation
1 Safe Node Implementation
2 Health Node Implementation
3 Edge gateway implementation
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9. Safe Node Implementation
A Power Management Unit
A rechargeavle battery
A voltage regulator MCP1810
Multi Control Unit(MCU)
Simblee with built in BLE function
LoRa module
RFM95
HoperRF Electronics Low power and long range transceiver
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10. Safe Node Implementation
Four Environmental Sensors
BME680(Temperature)
BME680(Relative humidity)
SI1145(UV)
GC0012(CO2)
Sensors are selected due to
High performance
High accuracy
Low power transmission
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11. Health Node Implementation
A power management Unit
Battery
RT6150, A low-power buck-boost converter
Multi Control Unit(MCU)
Simblee module with built in BLE
Two physiological sensors
MAX30205(Body temperature sensor) PPG(Heart rate sensor)
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12. Block diagram of the wearable sensor node
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13. Edge Gateway Implementation
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14. Software Implementation
1 Long Range Wireless Communication
2 Gateway Software Implementation
3 Cloud Implementaion
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15. Long Range Wireless Communication
Wearable network is based on a LoRa network
LoRa network is based on a star network topology
Data is transmitted from point to point
Data encryption is embedded to improve the security and privacy of
the network
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16. Long Range Wireless Communication
Mode of operation
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17. Long Range Wireless Communication
Wearable communication
Goal
The goal of wearable communication is to provide prompt safety warning
messages to all workers on site so that they can respond to emergency
circumstances as early as possible without getting notifications from the
gateway[5].
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18. Long Range Wireless Communication
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19. Gateway Software Implementaion
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20. Cloud Implementation
The cloud server is hosted in DigitalOcean that is an American cloud
service provider.
The server is running with Ubuntu 16.04.5 with 2GB RAM and 25GB
disk space.
A cloud-based website written on Node.js and Node-RED
A mosquito broker is configured as a bridge to connect the MQTT
broker in the gateway and the cloud.
MysQL database
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21. Conclusion and Future Scope
An IOT network system for connected health and safety applications
for industrial outdoor workplace is presented.
The system is able to monitor both environmental and physiological
data.
Aspects such as different hardware and software design and
implementations are discussed.
In our future work, different environmental and physiological sensors
can be integrated to the system to suit different workplaces.
A smartphone based IOT gateway can be developed to reduce the
dependency of fixed location gateway.
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22. References
[1] E. A. Rogers and E. Junga, Intelligent efciency technology and market
assessment, 2017.
[2] G. Aloi, G. Caliciuri, G. Fortino, R. Gravina, P. Pace, W. Russo, and C.
Savaglio, Enabling iot interoperability through opportunistic
smartphone-based mobile gateways, Journal of Network and Computer
Applications, vol. 81, pp. 7484, 2017.
[3] J. P. Dieffenderfer, E. Beppler, T. Novak, E. Whitmire, R. Jayakumar,
C. Randall, W. Qu, R. Rajagopalan, and A. Bozkurt, Solar powered wrist
worn acquisition system for continuous photoplethysmogram monitoring,
in Engineering in Medicine and Biology Society (EMBC), 2014 36th
Annual International Conference of the IEEE. IEEE, 2014, pp. 31423145.
[4] D. Robertson, Health effects of increase in concentration of carbon
dioxide in the atmosphere, Current science, pp. 16071609, 200
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23. References
[5] F. Wu, T. Wu, and M. R Yuce, An internet-of-things (iot) network
system for connected safety and health monitoring applications, Sensors,
vol. 19, no. 1, p. 21, 2019.
[6] M. Blumthaler, Uv monitoring for public health, International journal of
environmental research and public health, vol. 15, no. 8, p. 1723, 2018.
[7] D. Antoln, N. Medrano, B. Calvo, and F. Perez, A wearable wireless
sensor network for indoor smart environment monitoring in safety
applications, Sensors, vol. 17, no. 2, p. 365, 2017.
[8] J. Dieffenderfer, H. Goodell, S. Mills, M. McKnight, S. Yao, F. Lin, E.
Beppler, B. Bent, B. Lee, V. Misra et al., Low-power wearable
systemsforcontinuousmonitoringofenvironmentandhealthforchronic
respiratory disease, IEEE journal of biomedical and health informatics, vol.
20, no. 5, pp. 12511264, 2016.
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24. Thank You!
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