The Inventors Challenge Ceremony 2022

Background

Arm and All India Council for Technical Education have academic partnership and signed a Memorandum of Understanding in August 2019. Together, we have been enabling Engineering institutes build capabilities for the semiconductor ecosystem through grants from Arm Education over the years.

Arm Education and STMicroelectronics with support from AICTE’s Training and Learning Academy (ATAL) conceptualized and executed faculty workshops. 

In last 2 years we have conducted Faculty Development Programs on Embedded Systems, IoT, and AI/ML. 9000 faculty members and students have been trained on a pro-bono basis. 

As continuation of the workshops a contest “The Inventors Challenge-2022” was launched this year resulting in Faculty members and student teams converting their ideas into a prototype. 

The Inventors Challenge reiterated our belief on the importance of the industry-academia knowledge sharing. The initiative was well received and the feedback from participants has further strengthened our belief to continue such interactions.

The Inventors Challenge had 258 ideas submitted by faculty and student teams. The short-listed 22 teams received STM32 kits and industry mentorship to develop their idea into prototype. 7 Teams showcased the prototype to evaluators, business groups and guests at ST, Greater Noida Campus on 5^th December, 2022.

STMicroelectronics and Arm Education mentioned “It is a small step we have taken towards fostering the faculty and students in building Semiconductor capabilities and nurturing technology innovation. We believe these interactions with Industry exposes academic ecosystem to technological advancements”.

How did the activity benefit students:

The interaction with industry exposes them to technological advancements and nudges them towards innovation, kindling their interest in the semiconductor ecosystem.

How does the activity benefit Faculty

The faculty with the learnings could further strengthen their knowledge as well as curricula taught. The contribution of the faculty to build capabilities in the students goes a long way in nurturing the talent/innovators base.

Details of the finalists:

Team Details	Idea and Abstract
National Engineering College, Kovilpatti Dr. J. Naskath Venu Vignesh. T Maniazhagan. M Nithish Kumar. R Esakki Ram. R	Smart Fish Aquarium As a general rule of thumb, you need 1 gallon of water per inch of fish. Tiny tanks often lack filtration systems and heaters, which can lead to polluted, chilly water conditions that stress the fish. Stressed fish are more susceptible to diseases and will fail to thrive. Automatic fish feeders are electronic devices capable of dispensing fish food at preset intervals. It consists of a timing circuitry to keep track of time and a trigger or switch to activate the dispensing mechanism which usually employs a motor. The system supports remote dispensing where we can feed foods from anywhere using a Smartphone. The different sensors used to measure the physical and chemical parameters of the water are temperature, PH, oxygen, turbidity, TDS (Total Dissolved Salts). All the measured results are displayed on the monitor connected to the tank. The system triggers the oxygen motor whenever the oxygen level becomes lower. The smart fish tank also consists of a water purifier, which automatically absorbs ***, debris, and residues in water when the water purity level reaches a certain threshold. With the help of monitoring all the parameters, we can ensure the quality of water and also ensure the safety of the fish.
Sri Ramakrishna Engineering College, Coimbatore S. Jayanthy Kiruthika G Lakshana G Pragatheshwaran M Prassath A	Drone based early detection and location of an infected plant in cotton field Yield and growth of cotton plants are mainly affected due to bacterial diseases and pests. The solution proposed is to implement drone-based monitoring and edge AI for analysis. Drones will be integrated with an embedded system containing STM32L4R5 microcontroller and camera (B-CAMS-OMV) module for live data acquisition of cotton plant images. The images are processed using transfer learning algorithm to classify the diseases. GPS module integrated with the microcontroller will give the precise location of the infected plants. The type of disease and location is transmitted using a Wi-Fi module and can be viewed using a customized app in the mobile.
SRM Institute of Science and Technology, Ramapuram, Chennai K.Lalitha Aparnna Ajay Anusri.V	MLoRa32: A Safety Helmet for Mining Personnel   MLoRa32: A Safety Helmet for Mining” is a personal protective equipment (PPE) specifically designed for personnel in the mining field. The mining industry relies heavily on human resources because it requires physical labor. The workplace is filled with various known and unknown hazards which may even cause death. The existing system in the mining industry is not efficient in providing safety for workers.  IoT and AI in mining have brought positive change to personal health management. It is an intelligent module which can be embedded with the safety helmet of mining personnel. A complete set of safety features have been implemented as two units. First unit is a helmet unit and second unit is a control unit. Helmet unit consists of sensors namely BME680 (temperature humidity and gas sensor), MQ-135 (gas sensor) and pulse sensor. The helmet is also embedded with a voice transceiver, emergency alarm unit and a camera module. The control unit consists of an emergency receiver module, a display to view the sensor's output and a display to view the gesture given by the workers. Both the units are connected via a LoRa module. In addition to monitoring environmental conditions using the sensors, ML algorithm has been used to train the microcontroller to detect the gesture given by the worker. Here we have fixed 4 types of gestures which will help the workers to communicate. These gestures have been labeled as Good, Not Good, Doing Fine and Emergency Evacuation.
Amrita School of Engineering, Bengaluru Dr. Manju Khanna Gaurang Chaudhary Surisetty Hima Varshini Jammula Sathvik Samrit Saha	Smart Agriculture   Many of the agricultural problems in our country find their root cause in poor management. This may include the inability of deciding the right pattern of crops to grow, or which fertilizers to implement. The model aims to solve this problem by making use of IoT sensors to assess the various parameters of the farmland such as soil water level, temperature, pH level, etc. The model developed is a smart crop monitoring system which operates within an IoT infrastructure, makes use of AI and machine learning algorithms. These algorithms help the model to make prediction of the various parameters which aid the farmer in decision making. Since prediction requires historical data to make certain decision pertaining to the various parameters related to crops, a predefined agricultural dataset is used. The model also helps in providing recommendations with respect to which type of crops can be grown as well as which fertilizer would be beneficial for optimal results. These recommendations can be viewed on an application which would be available on a mobile device.
Saveetha Engineering College, Chennai Vasanth Kumar CH Aishree Ramesh Vincent Isaac Jeyaraj Jayashree Rao Lokesh Krishnaa	Gait detection and Analysis using IOT and Machine Learning IoT integrated with various/multiple sensors can detect irregular gait patterns. Sensors pick up the data and process it to check for gait patterns in an individual. AI and ML are used as leverage at present. Various developments have been made, since the inception of SACH (Solid Ankle Cushioned Heel), the first prosthetic foot, to improve the efficiency of the prosthetic leg to help correct abnormal gait. With rapid growth in AI and 3D printing, it has become easy to make efficient prosthetics. Machine learning models can be validated through various algorithms such as K-fold cross validation, stratified K-fold cross validation techniques, etc. to ensure data quality
Kumaraguru College of Technology, Coimbatore Jeya Daisy I Aakash S Sreeja GS Praveen E Arjun M	Labor pain and meconium detector This proposed idea is to help the hospital's staff nurses, non-Gyno physicians, and other supporting personnel in the rural area to determine whether a pregnant woman is indeed experiencing pain and complications which can alert the chief doctors if a problem arises during labor. This device can determine if discomfort is legitimate labor pain or not and also detect the cervical dilation, ejection, and rotation of the fetus are the comparative parameters that will recognize it early to avoid complications for both mother and fetus. An efficient X-NUCLEO-IKS02A1 controller, a cutting-edge measurement and sensor interfacing single-chip system, is used to measure them. Deep neural network-based computation will help to classify into three levels. They are Emergency (need a medical assistant), medium level and, Normal. Preprocessing techniques and feature extraction is done before classifications.  IoT is additionally designed for data transfer. A low-cost, IoT-based solution is suggested to track, archive, evaluate, and tag the vital signs data of pregnant women who live in rural areas experiencing labor discomfort and to transport them immediately if needed on the advice of the doctor in urban areas
Sardar Patel Institute of Technology, Mumbai Prof. Priya Deshpande Siddhant Kamlaskar Apoorva Limaye Varun Kamath	Structural monitoring of Roads using IoT We propose an IoT-based system for efficient, real-time monitoring of health and structural quality of roads using STM-micro-controller, accelerometer, gyroscope sensor and GPS module. The overall system will be compact, battery-powered can be attached securely to the lower side of daily commuting vehicles like garbage collection vehicles. The sensor-data first processed locally on the STM32 microcontroller using edge AI technologies then sent to the cloud for further processing. Finally, the reports can be viewed by the concerned road management authorities in the form of web application on a dashboard with exact location of roads with feedback mechanism of pending work.
Dr. Vishwanath Karad, MIT World Peace University, Pune Dr. Sumitra Narayan Motade Himanshu Rathod Omkar Boritkar Darshan Kadam Ananya Chakraborty Aniket Kulkarni	IoT based Blockchain Integrated Asset Tracking System Design using STM The central objective of the Asset Tracking System is to locate the position of assets and track other details with a decentralized Blockchain by using STM. The key goal is to guarantee extreme safety and allow tracing by providing desired parameters along with the location accurately and timely. With the combination of tracking and monitoring, this system secures assets and their positioning. STM in asset tracking can reduce the amount of power needed by the system to run and boost productivity with its features. Furthermore, blockchain can provide secure transactions, reduce compliance costs, and speed up data transfer processing.

Testimonials

• The workshop helped us understand about IoT in an easy way. Session was wonderful and informative- Meghashree M , Faculty, AIT, Chikkamagaluru

• Even though I had basic knowledge on IoT and ML after attending this workshop I have got confidence and strong knowledge. Dr. E. Kaliappan, Faculty, Easwari Engineering College

• Apart from theory sessions practical sections were included making it comfortable to understand the subject. Ravikant Kumar, Faculty, AISECT University

• More awareness than what I had. Like for example. I knew little on Arduino and Raspberry Pi3. STM looks like, it covers wide range of disciplines and end to end knowledge from micro controllers to plug in based on AI/ML intelligence incorporation. Dr. T. G. Vasista, Faculty, Pallavi Engineering College

• It was indeed a very pleasant experience of attending the workshop. For a person with Mechanical Engineering background, like me, the contents delivered during this workshop are really a great value addition. The speakers were experts in their domains and made the concepts very clear with case studies. The organization of the workshop was excellent, and I look forward to attending more such programs in future. - Dr Rupa Bindu, Professor of Mechanical Engg., Dr D Y Patil Institute of Technology, Pimpri, Pune

• Thanks to coordinating team, All the sessions are informative, given very good practical knowledge-Mallanagoud Patil, Faculty, V.P Dr. P. G. H. College of Engg. and Tech.

• These 5 days' workshop was very informative, and I enjoyed learning with live examples from the industry experts. Dr. P. Gnanasivam, Professor & Head, Department of ECE, Jerusalem College of Engineering

• The workshop made the understanding of IoT and Al/ML much easier then when I tried studying on my own. Tejas M.P, Student, Dayananda Sagar Academy of Technology and Management 

• It introduced me to a lot of new tools and frameworks to implement my ideas which were not known to me earlier. Apoorva Limaye, Student, Sardar Patel Institute of Technology

• To learn the subject by understanding rather than by rote learning is better for our future- Dhanush C, Student, Karpagam College of Engineering

• It is very useful and simple to understand form the well-known experienced lecturer. Shreeprasad Santosh Joshi, Student, St Xavier Technical Institute

• Earlier I’m not familiar with how the IoT and AI works, now quite clear about the concepts.  Jatin Ojha, Student, School of Computer IPS Academy, Indore

• It gave the so much information about development board and new ideas for the implementation.  Varun Sanghani, Student, PP Savani University

• Brought more clarity about what kind of data to be used for training model and got in depth clarity of some familiar concepts. Miloni Chetanbhai Patel, Student , Shrimad Rajchandra Institute of Management and Computer Applications