An autonomous wban implementation towards io t connected healthcare applications.
1. presented by:
Yogeesh M
ID:1DA17LDN08
Technical Seminar
on
An Autonomous WBAN Implementation
towards IoT Connected Healthcare
Applications.
Dr . AMBEDKAR INSTITUTE OF TECHNOLOGY
(An Autonomous Institution, Affiliated to V.T.U) BANGALORE-560 056
Under the guidance of:
Chandrakala V
Associate prof., Dept. of TCE
Dr. a I t
3. INTRODUCTION
• IoT is a new technological viewpoint that can connect things from various
field.
• For IoT connected health care applications, WBAN gaining its popularity.
• The proposed system proposes a wearable sensor node with solar energy
harvesting and Bluetooth low energy transmission.
• In WBAN various sensor nodes can be deployed on different positions of the
body.
• Web based smart phone application is used to display the sensor data . 3
4. • Solar energy harvester with MPPT technique is used to extend
the life time of the network.
• Here smartphone is used as gateway between the WBAN and
the IoT. As shown in fig 1
Cont.…
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5. SYSTEM ARCHITECTURE
• It consist of 3 major parts.
1. A flexible solar energy harvester with MPPT.
2. A wearable sensor node with BLE Transmission.
3. A smartphone application.
• Fig 2 shows the overview of the wearable sensor node.
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7. Micro-controller unit
• ATmega328P from Atmel®
• Low power, low cost and high performance.
• 8 bit controller.
• 32 KB flash memory.
• 2 KB SRAM
• RISC architecture.
• 6 analog input pins and 14 digital I/O pins.
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8. Flexible Solar Panel
• Photovoltaic module.
• Nonlinear semiconductor device.
• Absorbs energy of the light.
• MPT3.6-75.
• 7.2*6.0 CM^2.
• I-V characteristics is give by :
Fig 3: Electrical equivalence circuit of solar panel.
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9. Where,
• Iph Photo current
• Io Dark saturation current
• q Electronic charge
• ɳ Diode ideality factor
• K Boltzmann’s constant.
• T Temperature (Kelvin)
• Ipv Vpv & Ppv depends on Iph and T
• Fig.4 shows the I-V and P-V charecteristics.
Fig 4: I-V and P-V characteristics of a solar panel under
different irradiance level.
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10. MPPT circuit and Buck-Boost converter
• Maximum power point tracking technique.
• Extract maximum power.
• Buck-Boost converter is a type of SMPS.
• Buck converter Vi < Vo <0V
• Boost converter Same input voltage as input, to much higher level
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11. Supercapacitor
• Used as energy storage device.
• Electric double-layer capacitor
• accept and deliver charge much faster than
batteries.
• Typically stores 10-100 times energy per
unit volume
• tolerate many more charge and discharge
cycles than rechargeable batteries
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12. Accelerometer
• ADXL362 from analog Services ®.
• 3-axis MEMS accelerometer.
• Ultralow power consumption.
• Excellent temperature stability.
• ADXL362 is used for “fall detection”.
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13. Temperature and Pulse Sensor
• MAX30205 from Maxim®.
• High accuracy, high resolution
• Low power consumption.
• Provide over-temperature alarm.
• I^2C-compatible, 2-wire serial interface.
• SEN-11574
• To monitor the heartbeat.
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14. Bluetooth.
• HM-10 from Texas Instrument®.
• Communicating with IoS and android with 4.0
• Use 2.4GHz ISM band.
• GFSK modulation.
• 6 Kbps
• Range 100m
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15. Body temperature measurement and fall detection.
Monitoring of heartbeat.
MPPT circuit is used which extract the maximum power from
from the flexible solar panel.
Low power consumption.
A web-based smartphone application is designed to
sensor nodes data and can send emergency notification.
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ADVANTAGES
16. If flexible solar panel is covered with sun blocking objects,
generating electricity would be difficult.
The efficiency of the solar system drops during the
cloudy and rainy season.
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DISADVANTAGES
17. APPLICATIONS:
Medical emergency is one application area
for WBAN where couple of sensor will
monitor a patient’s activity and report if
something abnormal happens.
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Other applications of this technology
includes sports and military.
18. FUTURE SCOPE
A secondary battery can be used
as the backup energy storage in
case of bad weather conditions.
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19. REFERENCES
• Jamil. Y. Khan and Mehmet R. Yuce (2010). Wireless Body Area Network (WBAN) for Medical
Applications, New Developments in Biomedical Engineering, Domenico Campolo (Ed.), ISBN: 978-953-
7619-57-2,
• Wireless and mobile networks by dr.Sunilkumar s manvi.
• I. Lee and K. Lee, ``The Internet of Things (IoT): Applications, investments, and challenges for
enterprises,'' Bus. Horizons, vol. 58, no. 4, pp. 431-440, 2015
• R. Gravina, P. Alinia, H. Ghasemzadeh, and G. Fortino, ``Multi-sensor fusion in body sensor networks:
State-of-the-art and research challenges,'‘ Inf. Fusion, vol. 35, pp. 68-80, 2017.
• 3.F. Cicirelli, G. Fortino, A. Giordano, A. Guerrieri, G. Spezzano, and A. Vinci, “On the design of smart
homes: A framework for activity recognition in home environment,'” J. Med. Syst., vol. 40, no. 9, pp. 1-17,
2016.
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20. • 4.P. Gope and T. Hwang, “BSN-care: A secure IoT-based modern healthcare system using body sensor
network,” IEEE Sensors J., vol. 16, no. 5, pp. 1368-1376, May 2016.
• 6.T. J. Voss, V. Subbian, and F. R. Beyette, “Feasibility of energy harvesting techniques for wearable
medical devices,” in Proc. 36th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. (EMBC), Aug. 2014, pp. 626-
629.
• 7.T. Wu, M. S. Arefin, J.-M. Redoute, and M. R. Yuce, “A solar energy harvester with an improved mppt
circuit for wearable iot,'” in Proc. 11th EAI Int. Conf. Body Area Netw. (Bodynets), Turin, Italy, 2016, pp.
166-170.
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