SIH

BSN Sensor Node

• Hardware platform used : BSN Node
• Each BSN has three modules :
• BSN Node (Processor + RF Transceiver + Memory)
• Battery
• Sensor (physiological sensor like ECG, EEG, SpO2 etc)
• Processor : Texas Instrument (TI) MSP430F149 micro controller with 60KB + 256B of flash memory
• RF Module : Chipcon CC2420
• A USB programmer

Sink Node

• Battery Unit
• Lithium thionyl chloride
• TEG ( Thermo Electric Generator )
• GPS Module: Origin GPS
• Transceiver: Long Range Module (LoRa)
• Idle Transmission: GSM
• Microcontroller: ARM Cortex-M4 FPU-Based Microcontroller with 2MB Flash and 512KB SRAM
• Panic Button
• Network: Star Topology

Body Temperature Sensor

• A number of diseases are accompanied by characteristic changes in temperature.
• The Temperature Sensor will be programmed to send data only when there is a considerable change from the average temperature that affects the human body. In other times , the sensor will not transmit data while still collecting them and minimally processing them in its sensor processor.

ECG Sensor

• Monitoring for high/low values is important for detecting abnormal body conditions
• Abnormal heart rate can indicate a number of problematic symptoms— fainting, fatigue, chest pains, stroke etc
• Data Transmission - 15 seconds interval

Body Temperature

Sensor

Pulse Oximeter ( SpO2)

• It is identified as a crucial metric to protect against the onset of dangerous and potentially life-threatening conditions
• Helps in detecting Traumatic Brain Injury and Cerebral Desaturation
• Ability to calculate the heart rate from the same signals
• Data Transmission - 15 Seconds interval

ECG Sensor,

Pulse Oximeter

Soldier

Unit

Cuffless Blood Pressure Sensor

• Studies have shown that many soldiers die from hypertension than from combat .
• Higher readings of blood pressure are very serious and often require ‘immediate’ intervention.
• High reading of BP along with abnormal heart palpitations can indicate the onset of stroke.
• Data Transmission - 15 Seconds interval

Blood Pressure

Sensor

Sink

Node

Accelerometer

Accelerometer

• The accelerometers provide information on the sudden acceleration of a soldier subject to an external force (e.g. a bomb blast in the battlefield)
• Programmed to transmit data whenever there is sudden change in motion

Feature extraction

• Before sending the data to a base station or sink node directly.
• Data compression can effectively reduce the amount of data transmission.
• Data compression can lower power consumption effectively on BSN sensors, by reducing information stored in memory and transmitted by the transceiver.
• The methods can effectively relieve the pressure of low recognition accuracy.
• Power consumption is reduced.

Preprocessing

Data Compression

Data Fusion

CLOUD

Soldier

Unit

Actors of this system

• Soldier

• Squadron Leader

• Authorized operational center

LoRaWAN

• Out of the different wireless networks we have chosen LoRaWAN as network specification
• LoRaWAN is essentially a type of Low-power wide area network that allows battery-powered devices to connect over a large range of distances with the assistance of low bandwidth in any type of IoT network, ranging from regional to global depending on added specifications

Advantage

It eliminates the need for repeater and other infrastructure costs that are synonymous with the long range while significantly improving robustness to interference, noise and jamming,

while in this implementation, we are also personalizing each device with a unique 128 bit AES key, thus also making it a secure mode of transmission with a high rate of accuracy.

Gateway

Our Network specifications also include dedicated gateways, which are essential in a LoRaWAN while the overall structure is set up by connecting the base stations, in this case, the strap, with the local network of sensors directly.

Data Transmission level

• From the BSN coordinator (Sink Node) to the Cloud
• Data streams can be transferred onto the cloud through Transport Layer Security (TLS)/Secure Sockets Layer (SSL), which is a proven technology

Three Level Security Framework

Data management and access level

• Managing and accessing data and services on the cloud
• Data stored and processed in the cloud computing infrastructure need to be protected by authentication and authorization measures, and should be encrypted
• Moreover, the cloud services used by different actors of the system need to be secured through specific access control policies

Sensor Data Collection level

• Securing data communications from sensors to the BSN coordinator ( Sink Node) through encryption
• Wearable sensor nodes have limited computing and energy resources
• But encryption consumes time and energy, so specialized in‐node hardware needs to be exploited (e.g. 128‐bit AES encryption hardware is included in the TelosB sensor platform)

Framework

LoRaWAN

Private LoRaWAN networks comprise of :

• End-devices
• LoRa technology gateway

Mutual authentication is established between a LoRaWAN end-device and the LoRaWAN network as part of the network join procedure. This ensures that only genuine and authorized devices will be joined to genuine and authentic networks.

Encryption

Protection is provided by several layers of encryption:

• Unique Network key (EUI64) ensures security at network level
• Unique Application key (EUI64) ensures end to end security at application level
• Device specific key (EUI128)

LoRaWAN is one of the few IoT networks implementing end-to-end encryption.

These sensors are useful in inspecting some vital health parameters and give us a way to visualize, how health is affected on the battlefield.

Change in body temperature is a common symptom of some underlying health issue.The accelerometers provide information on the sudden acceleration of a soldier subject to an external force .

We have used sensors like body temperature sensor , pulse + and heart-rate sensor, and many more.

Blood oxygen level and pulse-rate both are very important to visualize health status. These both give us an accurate result with what actually the individual might be suffering.

• We can easily find out with these parameters adverse health conditions—including chest pain, shortness of breath and increased heart rate.
• Apart from the body sensors we have used GPS for all-time location tracking. This is very helpful as we can see the location, the climate at the location and how it affects the health parameters, the place where the actual enemies are located, the nearest help-center for that soldier and many more.

What next?

• Data gathered from the body sensors are transmitted in a continuous flow.
• In traditional methods of data processing the model is limited to the patterns it has observed in the static input file and cannot adapt to the real-time behavioral changes.

• Instead if we can use data directly with online machine learning algorithms which can work with real-time data.
• The real time data can keep improving our model and can help in better predictions.

Future Extension

• Furthermore, the proposed solution can be extended by using Satellites for communication as its signals can be found in most of the remote locations available
• There are also existing private channels available to our Nation's Defense Force
• This could be an enhanced, secure and efficient method of communication than ground level communication

Flow Chart

Eliminating Security Threats

The impact of security threats can prove to be a major issue.Some of the possible security threats are

• Man-in-the-Middle Attack
• Replay Attack
• Cloning Attack
• Denial of Service