A senior fall detection system is a technology that can automatically detect and alert when an elderly person falls. It can help prevent serious injuries or complications from falls that may take longer to recover from. Senior fall detection systems can be useful for seniors who live alone or have certain chronic health conditions that increase their risk of falling.
There are different types of senior fall detection systems, such as wearable devices, voice-activated wall buttons, or depth cameras. They can use sensors to measure the changes in the body position, physical activity, and acceleration of movements of the senior person. If a fall is detected, the system can send a signal to trained personnel, a caregiver, or an emergency service to help. Some devices also have GPS to allow seniors to remain independent and active.
It provides many benefits for older adults and their family members. It can reduce the response time and improve the outcome of fall-related incidents. It can also provide a sense of security and peace of mind for both the seniors and their loved ones. It can enhance the quality of life and well-being of the elderly population.
Therefore, a senior fall detection system is a promising technology that can help older adults prevent or cope with falls. However, it also requires further research and development to improve its performance and address its drawbacks. It also needs to be integrated with other interventions, such as fall prevention education, exercise programs, or home modifications, to reduce the risk of falls and promote healthy aging.
This tutorial will show you how to build a Fall detection system with UNIHIKER and Qubitro IoT cloud.
Step -1: UNIHIKER SetupFirst, we need to set up the UNIHIKER to find the fall movement. UNIHIKER has an inbuild Gyro and Acc. By using this we can easily build a fall detection system.
Use the Mind+ editor to connect with the UNIHIKER and create a new Python file. That will help to collect the ACC and Gyro readings.
To collect the Acc and Gyro readings we can use the ping-pong library.
import time
from pinpong.board import *
from pinpong.extension.unihiker import *
Board().begin() # Initialize the UNIHIKER
while True:
print(accelerometer.get_x()) # Read the value of acceleration in the X-axis
print(accelerometer.get_y()) # Read the value of acceleration in the Y-axis
print(accelerometer.get_z()) # Read the value of acceleration in the Z-axis
print(accelerometer.get_strength()) # Read the total strength of acceleration (combination of X, Y, and Z axes)
print(gyroscope.get_x()) # Read the value of gyroscope in the X-axis
print(gyroscope.get_y()) # Read the value of gyroscope in the Y-axis
print(gyroscope.get_z()) # Read the value of gyroscope in the Z-axis
print("------------------")
time. Sleep(1)
Here is the output response from the UBIHIKER.
Now we have the Acc and Gyro readings, next we need to make a fall detection system based on these readings. Here is the Python script that can classify the fall using Acc and Gyro readings.
import time
from pinpong.board import *
from pinpong.extension.unihiker import *
from unihiker import GUI
Board().begin() # Initialize the UNIHIKER
while True:
Ax = accelerometer.get_x()/16384.0
Ay = accelerometer.get_y()/16384.0
Az = accelerometer.get_z()/16384.0
Gx = gyroscope.get_x()/131.0
Gy = gyroscope.get_y()/131.0
Gz = gyroscope.get_z()/131.0
x=Ax*Ax
y=Ay*Ay
z=Az*Az
acc=x+y+z
a=acc**0.5*10000
if a<1:
string='static'
elif a>1:
string='Fall'
payload = {'Status': "Fall Detected", 'Log': "Alert"}
print(a)
print(string)
time.sleep(0.5)
Here is the UNIHIKER's response.
If the reading is above one, it will be considered as fall and it will print out the serial.
Step -3: Cloud SetupNow we have all our base setups, next we need to implement the IoT on the UNIHIKER to make an alert system when a fall is detected.
To build a cloud system, we are going to use Qubitro IoT cloud network.
Qubitro IOT is a cloud-based platform that allows users to connect, manage, and analyze their IoT devices and data. It can work with any IoT device that uses common protocols, such as MQTT or HTTP, regardless of the brand or model. Qubitro IOT also ensures the security and privacy of IoT data by using TLS/DTLS encryption and token authentication.
Qubitro IOT offers various tools and services for building and deploying IoT solutions, such as:
- Device management: Users can register, monitor, and control their IoT devices through a web portal or an API. They can also group devices by tags, assign roles and permissions, and update firmware remotely.
- Data management: Users can store, query, and visualize their IoT data using Qubitro’s built-in database and dashboard. They can also apply filters, aggregations, transformations, and alerts to their data streams.
- Data integration: Users can integrate their IoT data with other cloud services or applications using Qubitro’s connectors or webhooks. They can also use Qubitro’s REST API or MQTT broker to access their data from any platform or device.
- Data analytics: Users can perform advanced analytics on their IoT data using Qubitro’s machine-learning models or custom scripts. They can also use Qubitro’s widgets or charts to display the results of their analysis.
Qubitro IOT aims to simplify the development and deployment of IoT solutions by providing a scalable, reliable, and user-friendly platform. It also supports various IoT use cases, such as smart homes, smart cities, smart agriculture, smart industry, and more.
To create a new IoT connection in Qubitro, first log in to Qubitro Portal and create a new account.
Once you log in to the portal you will see this home screen,
First, we need to create a new project with all our credentials.
Then you need to create a new data source.
Select the connection type as MQTT.
Next, input all your details.
Once you are done, open the connection and the code snippet. You will see the example Python snippet to transmit data to Qubitro.
Just copy this code and use UNIHIKER to run this. Here is the Python script that can send data when a fall is detected.
import paho.mqtt.client as mqtt
import json
import time
from pinpong.board import *
from pinpong.extension.unihiker import *
from unihiker import GUI
Board().begin() # Initialize the UNIHIKER
broker_host = "broker.qubitro.com"
broker_port = 8883
device_id = "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
device_token = "XXXXXXXXXXXXXXXXXXXXXXXXXXX"
def on_connect(client, userdata, flags, rc):
if rc == 0:
print("Connected to Qubitro!")
client.on_publish = on_publish
else:
print("Failed to connect, visit: https://docs.qubitro.com/client-guides/connect-device/mqtt\n return code:", rc)
def on_publish(client, obj, publish):
print("Published: " + str(payload))
client = mqtt.Client(client_id=device_id)
client.tls_set_context(context=None)
client.username_pw_set(username=device_id, password=device_token)
client.connect(broker_host, broker_port, 60)
client.on_connect = on_connect
client.loop_start()
while True:
Ax = accelerometer.get_x()/16384.0
Ay = accelerometer.get_y()/16384.0
Az = accelerometer.get_z()/16384.0
Gx = gyroscope.get_x()/131.0
Gy = gyroscope.get_y()/131.0
Gz = gyroscope.get_z()/131.0
x=Ax*Ax
y=Ay*Ay
z=Az*Az
acc=x+y+z
a=acc**0.5*10000
if a<1:
string='static'
elif a>1:
string='Fall'
payload = {'Status': "Fall Detected", 'Log': "Alert"}
client.publish(device_id, payload=json.dumps(payload))
print(a)
print(string)
time.sleep(0.5)
Just run the Python script, if any fall is detected it will send data to Qubitro.
If any fall is detected, it will send data to Qubitro.
Here is the response from the Qubitro IoT cloud.
Next, we need to make an alert system that can send an SMS when a fall is detected.
Step -4: Alert SetupNavigate to the functions in the Qubitro menu and create a new function.
Add a new rule setup.
Create a new rule setup with a specific option.
Here you can configure your specific alert setup as you need
Wrap-Up:Finally we have our own fall detection system with the help of UNIHIKER and Qubitro.
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