Page 18 - nai udaan march 2024

Projects and Achievements of Lab

1. EGG INCUBATOR:

The students Upanshu Singh, Md Armaan Alam, Rao Atif Ali, Shivansh Thapliyal
from Dr. B.R. Ambedkar School of Specialised Excellence (SOSE) in Kalkaji, Delhi.
Within the Rashtriya Avishkar Abhiyan (RAA) Lab, their ingenuity took flight as they
meticulously designed an egg incubator. This ingenious creation not only nurtured
life but also clinched first place at the zonal level. Their tireless efforts, guided by
curiosity and passion, transformed wires into whispers of possibility. Temperature
sensors danced, relays clicked in harmony, and within the cozy confines of their incubator,
life stirred—a testament to their dedication and scientific spirit. These young minds
have hatched more than just success; they’ve ignited a beacon of innovation within the
RAA Lab.

2. Somnolence Prevention

The project somnolence prevention was made to prevent the roads accidents, as the main
of road accidents is drowsiness or failure of attention on read while driving, this device
aimed to prevent the drowsy person from driving the vehicle and wake him up. Jayant
Chauhan Won 1rst prize in State level for his excellent idea and innovative project.

3. Low-Cost C.P.A.P machine

Sleep apnea is a disease which occurs in people having double chin, mostly in older
ages which causes blockage of wind pipe while sleeping and can even cause death in
some cases. People suffering from this condition have to sleep with a machine which
act as their artificial lung helping them to breath but it can cost several lakhs. Our
students Yogita Singh and Chunmun of class 12th along with Md Armaan Alam and
Upanshu Singh of class 11th designed a low cost machine for the common people of
India. The project not only bagged first position at zonal level but also secured 2nd
position at state and went to Centre level.

4. Smart Driving Assistant

The Smart Driving Assistant project presented at the science exhibition operates
through a sophisticated system comprising a camera, Raspberry Pi, and Python pro-
gramming. The project's mechanism involves the camera capturing real-time road
imagery, which is then processed by the Raspberry Pi using Python scripts. Leveraging
image recognition algorithms, the system identifies road signs, traffic lights, and
potential hazards, subsequently providing timely alerts and assistance to the driver.
This innovative integration of technology with computational thinking principles not
only enhances road safety but also offers insights into future advancements in driving
assistance systems, with implications extending beyond the exhibition context.

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