Ideaz

Have you ever bought a tub of Greek yoghurt and then forgotten about it? A week later, you find it in your fridge, already expired. Not only is this wasting your money, but it is also wasting food. If something like that ever happened to you, then this app is perfect for you. 

My idea:

My idea is to develop an app that tracks the expiration dates of groceries purchased by consumers. All the consumer has to do is scan the barcode of the groceries, and the app then adds it to its list. It sends reminders about any food expiring soon and also suggests dishes based on the ingredients available in the list. 

Gaps in the current market:

The current market doesn't really combine the barcode scanning of groceries with giving recipe recommendations. Also, this app will focus more on the products and companies found in the Indian market. 

Who benefits:

People who are forgetful about their groceries (like me) are gonna benefit a lot from this app. Apart from that, the general public can also use this app, which decreases food waste as people won't wait till their groceries expire. Reducing food waste is going to help everyone achieve a more sustainable world. 

Why this problem matters to me:

This problem matters to me because I see tons of food wastage around me daily, whether it be in the campus mess or in the general public. I believe minimum food wastage is going to benefit the people. This app is also going to minimise the financial waste from households, which will help them have a better budget. 

Technical details:

• Built with React Native (iOS + Android).
• Barcode scanning via ML Kit with a manual entry option for items without a barcode.
• Colour-coded expiry indicators and notifications.
• Recipe recommendations based on which product expires first. 
• For produce, it uses estimates of when it expires (eg: an apple 5-7 days).

Communication is the foundation of human connection, yet millions of deaf and mute individuals face barriers every day. From ordering food at a restaurant, to visiting a doctor, to working in an office—simple conversations become complex when others don’t understand sign language.

Currently, some apps and devices try to translate sign language, but they face big challenges: translations are often inaccurate, real-time processing is slow, and they don’t adapt to different regional sign languages. On the other hand, solutions that convert speech to text exist, but they don’t bridge the full gap—mute individuals still cannot easily express themselves back in spoken form.

Gaps in Current Solutions:

• Lack of real-time, accurate translation of sign language into speech.

• Limited tools that can convert voice into signs or actions for deaf/mute individuals.

• Existing solutions are often costly and not user-friendly.

• My solution: SignSpeak – a smart assistant to make communication seamless.

How it works:

• ✋ Sign-to-Speech: Using AI and camera recognition, the system detects hand gestures and body movements, instantly translating sign language into spoken words.

• 🎙️ Speech-to-Action/Text: Converts spoken language into text or visual actions, enabling deaf and mute users to understand and respond quickly.

• 📱 Cross-platform: Works on smartphones and wearables, making it affordable and portable.

• 🌍 Inclusive: Supports multiple languages and regional sign variations.

Who benefits?

• Deaf & mute individuals → Gain confidence and independence in daily communication.

• Families & friends → Build stronger bonds without the constant need for translators.

• Schools & workplaces → Create more inclusive environments.

• Community → A step toward equal opportunities and breaking social barriers.

💡 Why this matters to me: I believe communication is a basic human right. Too many people are left out of conversations simply because they communicate differently. By turning signs into speech and speech into actions, we can create a world where everyone is heard and understood.

Problem statement 

Recently there have been close calls in the avation sector, mainly with airplanes; a primary example would be that an Air India flight is taking off from the run way, and an Indigo flight is trying to land on the same run way at the same time, both these planes were very close to each other, and would have collided if not for a 2-3 second difference. This was just one example, there have been multiple incidents like these in relation to flight safety mainly due to errors caused by the Air Traffic controllers. The air traffic controllers have very irregular timings, and just imagine the reduction in the efficiency of those ATC who are working during the night hours (night shifts). 

Gaps 

The air traffic is mainly managed by humans, and we can't take a chance with peoples lives. And there has not been any AI/ or an AI agent for an air traffic controller.

Solution 

We can have an AI agent, which is able to detect the incoming flights on the radar, the agent is automatically able to assign which flight will come for landing on which runway and at which time, based on an ML algorithm. We are able to maintain a significant distance between both planes ie greater than 5 miles, which is crutial for flight safety. The goal is to reduce the hassle and the stress the air traffic controllers take. The algorithm will have many parameters such as the fuel remaining, time remaining for landing, presence of a mayday call, presence of a pan call, number of souls on board, weight of the aircraft, presence of an emergency, physical and mental condition of the pilots, total time flown so far and many more critical factors.

So the AI considers all these parameters, where each parameter will have its own priority, for example a Mayday call will have the highest priority. And the flight having the highest priority will be allowed to land first....

Benefits

Using AI to make the take off and landing clearance calls to prevent such massive disasters, will evade a ton of stress among the ATC because one air traffic controller is responsible for 15-20 flights. We are also saving a lot of time, becasue the AI is able to give multiple calls to various pilots at the same time. It may not saves lives directly, but it does indirectly. If there is a crash due to the ATC being fatigued, this will cost lives, using an AI agent we could have prevented such a painful accident.

Why it matters to me 

Life is the most important thing on this planet, We must forget all the money and status, the most amazing thing in the world is simply being alive. Life is the one gift that makes everything else real it’s the beautiful, messy chance we have to genuinely love and care for one another.

In today’s fast-paced world, people often face difficulties finding reliable service providers for household needs such as refrigerator repair, washing machine servicing, plumbing, or electrical work. Currently, most people depend on word-of-mouth, local shops, or unverified online numbers, which are often unreliable, overpriced, or time-consuming to arrange. My idea is to create a service-providing app that allows users to easily book verified professionals for their specific needs with just a few taps.

This app will solve the real-world problem of connecting customers with trusted technicians. It will act as a one-stop platform for multiple services—home appliance repair, home cleaning, carpentry, plumbing, painting, and more. Users can search, compare, and book a service provider based on ratings, reviews, price transparency, and availability.

The current market has fragmented solutions, where one app focuses on only food delivery, another on cab rides, and some limited ones on household services. However, there is no comprehensive, trustworthy solution that covers a wide range of essential home and office services under one roof.

Who benefits?

• Users/customers: Save time, avoid fraud, and get quick solutions at fair prices.

• Service providers/technicians: Gain steady work opportunities and build reputation through verified ratings.

• Community: Encourages formalization of unorganized service sectors, ensuring safety and trust.

This problem matters to me because I have personally seen people struggle when urgent home repairs are needed, but finding a reliable technician becomes a huge hassle. With such an app, we can make life more convenient, safe, and efficient for everyone.

Technical details (optional): The app will use location-based search, secure payment gateways, real-time tracking of technicians, and verified user profiles to ensure safety and transparency.

Every one of us has faced inconveniences during our hostel stay. It could have been roommate issues, noisy neighbours, or maintenance troubles. Today, I want to offer a solution to at least one of these problems.

When I moved into the hostel, my cupboard came with a very rusty closet rod. As someone with very sensitive skin, I started getting rashes as the rust fell on my clothes. Sharing bathroom stalls with dozens of people can be frustrating, especially when cleaning or repairs take longer than expected. Like many others, I quickly discovered that maintenance issues - from broken fixtures to leaky pipes - can become a daily inconvenience when repairs aren’t addressed promptly. 

We did have a solution: A physical complaint register. We had to fill it up if we had any problems, and the warden would then place a request with the repairman to fix the issue.

The existing solution, however, came with its own set of challenges. Firstly, we had no idea when the repairman would come to fix an issue. This left room for embarrassing moments like plumbers walking into the bathroom while it was in use, or carpenters entering rooms while students were changing.

These are very common issues for people living in hostel accommodations. Many have even come to see these “minor inconveniences” as a normal part of hostel life. Funnily enough, all of these inconveniences can be resolved with a very simple solution: an app.

On this app, students will be able to directly report their concerns and upload pictures with a description of their issue. The repairman will instantly be notified of the issue, eliminating the middleman communication that causes delays. But where does AI come into play here? We can smartly implement an AI to optimise the repairman’s schedule, minimizing the number of trips he needs to make. The schedule can be made publicly visible, giving everyone an exact time of when said issue will be resolved while preventing embarrassing moments for all parties. The AI model can also be used to organise the tasks based priority with higher priority issues being pushed up. This also helps out the wardens and other support staff who would otherwise have to manually categorise all these tasks.

A simple app like this can have a huge impact on one’s hostel stay. It is not just a solution for the residents, but improves the lives of the repairmen, the wardens, the cleaners and all the staff involved in hostel maintenance.

The Problem
Stray dogs wandering on busy streets often cause accidents while searching for food. They gather around garbage piles or run across roads, putting themselves and drivers at serious risk. Current efforts such as sterilization and awareness campaigns help in the long term, but they don’t solve the daily issue of dogs entering high-traffic zones in search of meals. This gap results in repeated accidents, animal suffering, and unsafe roads for everyone.

The Solution
SafeBowl is a community-driven initiative to set up designated feeding and water stations for stray dogs in safe, traffic-free areas. These stations include food dispensers that release meals at fixed times and bowls of clean water, training dogs to gather at predictable, safe spots instead of on the road.
To make the system sustainable, SafeBowl works on an “Adopt-a-Station” model, where shop owners, residents, or volunteers manage specific stations with municipal support. Over time, strays associate these spots with reliable food, reducing their presence on busy roads.

Impact and Benefits

• Stray dogs: Safer, healthier, with consistent access to food and water.
  
  
• Drivers/commuters: Reduced road obstructions and accidents.
  
  
• Communities: A kinder, safer environment where animal welfare and public safety go hand in hand.
  
  

Why This Matters to Me
I adopted a stray dog from a shelter who had been badly injured in a bike accident. Seeing her pain made me realize how dangerous roads are for animals and how small interventions can prevent such suffering. SafeBowl is my way of addressing a problem I’ve personally witnessed—making streets safer for both humans and strays.

Technical Details

• Timed food dispensers and water bowls at designated locations.
  
  
• Low-cost stainless steel or gravity-based designs initially.
  
  
• Future upgrade: smart dispensers with sensors to track usage and send refill alerts.
  
  
• Optionally, reflective paint or solar lights for better visibility at night.

OVERVIEW:-
Traditional wildlife monitoring is labor-intensive, invasive, and lacks real-time capability, limiting effective conservation. There is a need for an automated AI-based system to accurately detect and track wildlife, providing timely data, early threat detection, and stronger support for ecological research.

Gaps:-

1. Lack of real-time monitoring; data is often delayed.
2. Poor scalability across large or remote areas.
3. Limited integration of multi-source data (satellites, drones, sensors).
4. Errors in species identification.
5. Complex data management with few user-friendly platforms.
6. Minimal community engagement or citizen involvement.

Who Benefits:-

• Rangers and enforcement agencies: quicker detection of threats like poaching.
• Wildlife tourism: healthier ecosystems boost eco-tourism.
• Local communities: gain education, jobs, and incentives for conservation.
• Environmental organizations: better data to guide and prove impact.

Why It Matters To Me:-
Conserving wildlife protects biodiversity, ecosystem balance, and essential services like pollination, climate regulation, and clean water. It also supports sustainable livelihoods, tourism, and fulfills our ethical duty to protect nature for future generations.

Technical Details:-

• Sensors: thermal, infrared, motion detectors.
• Security: encryption, authentication, blockchain.
• Processing: edge/cloud computing for real-time alerts.
• Integration: camera traps, drones, satellites, acoustic sensors, eDNA sampling.

Startup Vision

We aim to create Human-Assistive Robotics — affordable and intelligent robotic systems that restore independence, safety, and dignity to people with mobility challenges.Our approach fuses practical mechanical design with accessible AI to make our technology both smart and reliable, making advanced mobility tools accessible to everyone, not just the privileged few.

The Problem

Traditional mobility aids like crutches, walkers, and wheelchairs are outdated. They cause discomfort, demand physical effort, and fail on uneven terrains such as slopes and stairs. Advanced prosthetics and robotic aids exist, but their cost and complexity make them inaccessible for the majority, especially in developing countries. This leaves millions of elderly and disabled individuals dependent, unsafe, and underserved.

The Solution

Our first step is Robotic Crutches — intelligent walking aids that self-adjust to height and terrain, monitor balance, and prevent slips. With sensors and AI-powered gait analysis, these crutches adapt to individual walking styles while remaining lightweight and affordable. They give users safer, more comfortable mobility and and serve as the first step toward our ultimate goal of developing prosthetics, exoskeletons, and other robotic aids to empower daily living.

Value Proposition

• For Patients & Elderly: Greater independence and safety.
• For Families & Caregivers: Peace of mind through smart support.
• For Healthcare: Rehabilitation tools that enhance recovery.
  

Expanding Our Impact:

• Restoring Limbs: Engineering affordable, modular robotic arms and legs.

• Augmenting Strength: Building exoskeletons for workforce support and physical therapy.

• Enabling Navigation: Creating smart wheelchairs that can avoid obstacles and navigate independently.

• Recovering Function: Designing a robotic glove to restore grip strength for stroke patients.
  
  
  

Sun & Rain Canopy for Two-Wheelers

The Problem:-

In India, two-wheeler riders make up more than 70% of daily commuters. Unlike car drivers, they are exposed to harsh sun, sudden rains, and dusty winds while waiting at traffic signals or during slow traffic. This leads to:

Health issues (heat strokes, dehydration, skin problems).Discomfort and stress during travel.

Safety risks when riders try unsafe hacks like balancing umbrellas or rushing red lights to avoid getting wet.

Existing solutions like raincoats or ponchos are inconvenient, while big fixed sheds at signals are costly, hard to maintain, and not scalable across Indian cities.

The Gap in Current Market:-

Sepal (India, Shark Tank): Provides full motorcycle canopy but costs ~₹10,000, too expensive for many. Bulky and not stowable quickly.

Umbrella-type attachments (Amazon, Qaswa, Muren, etc.): Cheap but unsafe, unstable in wind, and block visibility.

Government infrastructure sheds: Expensive, space-hungry, not available at every signal.

 Gap: No affordable, lightweight, foldable canopy that is safe, quick to deploy, and rider-friendly.

HOW MY IDEA SOLVES:-

Design a foldable bike-mounted canopy that can be deployed like an umbrella when the bike is stationary (e.g., at signals, in traffic jams) and stowed away before riding.

Key features:

• Lightweight (≤ 4–6 kg), mounted on rear grab rail.
• Telescopic scissor mechanism (manual pull-up & lock).
• Waterproof + UV-protected fabric with vents for wind stability.
• Reflective strips for visibility.
• Quick-release system to fold and stow within seconds.

Cost target: ₹2,500–5,000 (affordable mass-market).

Who Benefits:-

Daily commuters on bikes/scooters: Protection from sun, rain, dust while waiting.

Families & delivery riders: Comfort for pillion riders, especially children and elderly.

Community & cities: Safer traffic behavior (riders won’t jump red lights to avoid weather), healthier and happier citizens.

Why This Matters to Me:-

Every day I see bikers waiting at red lights under scorching heat or heavy rains, getting drenched or exhausted, while cars wait comfortably. I believe two-wheeler riders deserve equal dignity and protection. This idea is close to me because it’s about fairness, comfort, and everyday safety for millions of Indians who rely on bikes.

 Technical Details :-

Frame: Aluminium alloy for lightness.

Canopy fabric: PU-coated polyester (waterproof, UV-resistant).

Mechanism: Telescopic scissor arms with locking joints.

Safety: Designed only for stationary use (interlock reminder to stow before riding).

TAGS:-

• mobility, two-wheelers, biker safety, rain protection, sun protection, affordable innovation, urban commuting, smart canopy

Problem

The traffic congestion due to poor management of signals is a major problem in India. During my daily trips to university and home, I often find myself wasting time at red lights that serve no purpose because there is no traffic at the other intersections. Not only does this delay travel, but it results in wasted fuel, added emissions and unnecessary stress for commuters. Especially near my house , the police have to stop the traffic signal completely and manually control the traffic everyday as there is more traffic on one side of the road.This problem affects me personally as I reach home late almost everyday disrupting my university-life balance. The challenge is more critical with developing cities as the traffic is unmanaged and varying at maximum extent in a day.

What Already Exists

At present, most traffic signals in Indian cities work on pre-fixed timings. The red, yellow and green phases are predetermined according to historical traffic surveys. For instance, the traffic signal may stay green one way for 60 seconds, and the other 30 seconds, with no regard for whether cars are queued up or not. Some cities like Bengaluru, Delhi or Hyderabad have implemented the use of adaptive traffic control systems with pre-deployed sensors, inductive loops and high-resolution cameras. They time themselves in real time according to the flow of vehicles.

Why the solutions are not ideal

Fixed-time systems have become outdated due to their inability to adapt in case of sudden variation like an accident, festival rush or late night empty road. So many vehicles are unnecessarily idling, which leads to increased commute times and wasted fuel. Adaptive solutions available in metro cities, on the other hand, are expensive. The infrastructure of high end cameras, underground sensor loops and networking take a heavy investment and maintenance , in dusty and monsoon India, where power can be irregular , these systems frequently fall apart. When they fail, police officers have to step in the road and manage circulation. This is the opposite of automation. Also, there is no easy way to expand these expensive systems to smaller towns, making a majority of the country with inefficient fixed time signals.

What We Can Do Better 

With my limited knowledge of programming and algorithms, this is the best solution I can come up with. I studied MySQL and databases in grades 11 and 12, and I feel that this could be a decent approach to solving everyday traffic problems.

A more affordable adaptive solution might be found with less complicated sensors and more intelligent software. Options that are far cheaper than expensive buried loops or state of the art AI cameras, such as: 

• Infrared vehicle counters: inexpensive, weather-resistant, and easy to mount on poles.
  
  
• Basic CCTV cameras with open-source image recognition: software-based processing reduces hardware cost.
  
  
• RFID readers for buses and emergency vehicles: ensures public transport and ambulances get priority without human help.
  
  
• Solar-powered traffic lights: cuts down electricity bills and prevents signal failures during power cuts.
  
  

At the heart of the system will be a MySQL database, which stores traffic information in real-time and over time. Each signal measures: road ID, time, vehicle volume and average headway. The algorithm operates based on these data and questions this data in order to control green light dynamically. Algorithm Outline Input: The number of vehicles on the sensors at each scanned road attached to the signal.

Decision:

If one road has no cars → switch the green light to that with waiting cars immediately.

If there is a queue long enough (Q > Threshold) we should be giving them green.

In the peak periods → apply historical database information to pre-assign longer green times.

Enforce fairness so that no road waits indefinitely.

Output: Automatically update signal cycle, write new timing to the database.

Cost Savings Installation: The cost of infrared sensors and open-source software is significantly lower than that of imported adaptive systems.

Power: Solar lights are energy-saving and environmentally-friendly with high-quality.Solar powered outdoor lights are cost-effective because they are very energy efficient. Reduce your electricity costs and save you money.

While not immune to abuse and damage, LoopBox and Trailblazer are both resistant to dust, moisture and rain. Easy-to-replace sensors mounted above the road are far superior compared to wires that run in a trench under the road.

Scalability: Because it is affordable, this system can be adopted in smaller cities and towns that cannot afford expensive smart-city projects.

Reduced Police Intervention : Presently, traffic police jump signals during peak hours or in case of a signal failure. With this system: Instant detection eliminates the need for officers to be stationed on busy crossroads.

A single monitoring dashboard makes it possible for a few officers to monitor numerous intersections from afar.

Emergency vehicles can be automatically identified with RFID tags, without reliance on manual police cooperation.

Who It Benefits 

This will help a lot of people such as daily commuters (by cutting wait times) , smaller towns where the budget is limited , public transport and emergency vehicles like the ambulance move faster as signals are prioritised , and the traffic police who can focus on solving problems such as taking care of people who have no common sense to follow traffic rules. 

Small sample code on storage of data : 

CREATE TABLE trafficdata (

    signal_id INT,

    road_id VARCHAR(20),

    timestamp DATETIME,

    vehicle_count INT,

    avg_wait_time FLOAT,

    PRIMARY KEY(signal_id, road_id, timestamp)

);

IR vehicle counters (₹2k–5k), basic CCTV with open-source software on Raspberry Pi, and RFID tags for buses/ambulances. Solar-powered units cut energy costs, while a phased rollout installs sensors only on major roads.

In this 21st Century, use of Technology is being rapidly increased and everything in the present world is being operated through cellphones. A business setup too provides a TECH SUPPORT service made for senior citizens can be helpful. Senior citizens often face many challenges with technology, creating a strong market opportunity.
A Specialized service that offers patient, personalized technology support that can address a critical need and create a profitable, mission driven business.

Services Offered:-
The business will provide a range of in-home and remote technology assistance services, including:
Device Setup and Troubleshooting:
• Setting up new devices (smartphones, tablets, computers, smart TVs).
• Connecting to Wi-Fi and other home networks.
• Troubleshooting common issues (e.g., slow performance, application errors).
• Personalized Training:
• One-on-one lessons on specific applications (e.g., video calling apps like FaceTime or Zoom, social media, email).
• Teaching online safety and fraud prevention.
• Instruction on using digital services for banking, healthcare, and shopping.
Home Automation and Safety Technology:
• Installing and explaining smart home devices (e.g., voice assistants like Alexa, smart lighting, security cameras).
• Setting up medical alert systems and health monitoring devices (e.g., fitness trackers, blood pressure monitors).
Software and Application Support:
• Assisting with software updates and installations.
• Helping with photo and document organization.
• Configuring accessibility settings (e.g., larger fonts, screen readers).
This idea seems to be important to me as an individual because regardless of age, understanding the needs of senior citizens is an important step toward creating a more inclusive, empathetic, and connected society. This business idea is one way to contribute to that goal while also creating a viable and meaningful startup idea.

Food delivery services like Zomato, Swiggy, and Uber Eats have transformed how we enjoy restaurant meals at home. But there’s one major problem: by the time food arrives, it often turns cold or soggy, losing the fresh taste it had when prepared. Pizzas lose their crispness, dosas become soft, and noodles get clumpy. While some countries like Japan and Korea use self-heating meal kits, no affordable, eco-friendly, and scalable solution exists for everyday food delivery across the world.

Current options have clear gaps: heated bags keep food warm but trap moisture, making food soggy; single-use chemical heaters create waste and safety concerns; electric warmers need costly charging setups; and temperature control is often inconsistent for longer deliveries.

My solution: a Smart Self-Heating Food Parcel that solves all these problems. It uses a heat storage layer to keep food warm naturally, a small heating pad for extra warmth when needed, and steam vents so crispy foods stay crisp. The swappable battery system makes it easy to recharge, and the reusable outer shell with recyclable liners keeps it eco-friendly and cost-effective.

This solution would benefit restaurants, delivery platforms, and customers alike: restaurants can maintain quality standards, delivery services can improve customer satisfaction, and consumers get fresh, hot meals at home. Moreover, by using eco-friendly materials and scalable production methods, this technology could be made affordable and sustainable for mass adoption.This problem matters to me because hot, fresh food is a simple joy everyone deserves, and with the booming food delivery industry, we need innovations that elevate convenience without sacrificing quality or the environment.

One of the daily struggles for students is transportation within and around the university campus. Walking long distances in the heat, waiting for crowded shuttles, or relying on expensive auto-rickshaws consumes valuable time and energy. For students who stay late in labs or libraries, safety and reliability become even bigger concerns.

My idea is to introduce CampusRide, a student-run electric bike and scooter sharing system designed specifically for university life. The service would allow students to unlock e-bikes or e-scooters using their student ID card or a simple mobile app. Vehicles can be parked at designated docking stations around campus — near hostels, libraries, cafeterias, and academic blocks.

The pricing would be highly affordable, with pay-per-use or monthly subscription models, making it budget-friendly for students. Since the system uses electric vehicles, it is eco-friendly, reduces carbon footprint, and promotes green mobility inside the campus. Additionally, the app can integrate safety features such as GPS tracking and SOS buttons for late-night riders.

This solution benefits:

• Students: Saves time, provides convenience, and improves safety.

• University: Promotes sustainability and enhances the campus image.

• Community: Encourages adoption of clean and smart mobility.

As a student, I believe this idea matters because it addresses our everyday struggles while contributing to a greener and smarter campus environment. With the right support, CampusRide could become a model that other universities adopt too.

The absence of robust auto-correct and prompt enhancement features in large language models (LLMs) like ChatGPT and Gemini presents a significant real-world problem. Unlike typical text editors or search engines that offer spell-checking and query refinement, current LLM interfaces largely leave the burden of crafting effective prompts entirely on the user.

Gaps in Current Solutions/Market

1. Lack of Real-time Prompt Correction: There's no equivalent of "Did you mean?" for LLM prompts. Typos, grammatical errors, or awkwardly phrased questions can lead to suboptimal or irrelevant responses, without the user being alerted to the potential issue.

    

   

   
   

    

2. Absence of Prompt Enhancement Suggestions: Users often struggle to formulate prompts that elicit the best possible responses. Current interfaces don't offer suggestions to make prompts clearer, more specific, or to add context that would improve the LLM's output. For example, suggesting adding "in the style of a formal report" or "provide five bullet points" could significantly improve results.

    

   
   

    

3. Limited Contextual Understanding of User Intent: While LLMs are powerful, their ability to interpret user intent from poorly constructed prompts is still limited. A prompt enhancer could bridge this gap by suggesting ways to align the prompt more closely with the user's underlying goal, even if the initial phrasing is imperfect.

4. No Feedback Loop for Prompt Quality: There's no inherent mechanism within most LLM interfaces to help users learn how to write better prompts over time. A system that offers suggestions and corrections could serve as an educational tool.

Who Benefits?

• Users:

  • Reduced Frustration: Less time spent guessing how to phrase a prompt to get the desired output.

  • Improved Output Quality: More accurate, relevant, and comprehensive responses from LLMs.

  • Increased Efficiency: Quicker task completion due to fewer iterations needed to refine prompts and responses.

  • Accessibility: Users with writing difficulties or non-native English speakers would particularly benefit from automatic corrections and suggestions.

  • Learning: Users can learn to craft better prompts by observing the suggested corrections and enhancements.

• Buyers (Businesses/Developers):

  • Higher User Satisfaction: More effective use of LLM-powered applications leads to happier customers.

  • Reduced Support Load: Fewer user complaints about poor LLM output that stems from inadequate prompting.

  • Increased Productivity: Employees using LLMs for tasks (e.g., content generation, data analysis, coding) can work more efficiently.

  • Better Data for Model Training: Cleaner, more effective prompts could provide better data for future LLM fine-tuning, as the interaction history would represent more optimal use cases.

• Community:

  • • Democratization of LLM Use: Lowers the barrier to entry for effectively using powerful AI tools.

    • Innovation: A more effective prompting experience could unlock new applications and use cases for LLMs that are currently hindered by poor prompt formulation.

    • Ethical AI Use: By helping users articulate precise requests, it might reduce the generation of undesirable or biased content stemming from vague or ambiguous prompts.

   

  Why This Problem Matters to an Undergraduate Student (like myself)

  For an undergraduate student, LLMs are increasingly indispensable tools for:

  • Research: Summarizing articles, finding information, brainstorming topics.

  • Writing: Drafting essays, reports, creative pieces; generating outlines.

  • Coding: Debugging, generating code snippets, understanding concepts.

  The absence of auto-correct and prompt enhancers directly impacts a student's academic performance and efficiency:

  1. Time Waste: Students often spend valuable time tweaking prompts, experimenting with different phrasings to get the right output. This time could be better spent on actual learning or project work.

  2. Suboptimal Results: A poorly phrased prompt can lead to generic, irrelevant, or even incorrect information, forcing the student to double-check everything manually or abandon the LLM's output.

  3. Learning Curve: Students new to LLMs might get frustrated quickly if they can't effectively communicate their needs, potentially underutilizing a powerful learning resource.

  4. Academic Pressure: In a high-stakes academic environment, getting precise and helpful output from an LLM can be crucial for meeting deadlines and achieving good grades.

  5. Skill Development: Learning how to effectively "talk" to AI is a valuable skill for future careers. Prompt enhancers could accelerate this learning process.

   

  Technical Details 

  Implementing prompt auto-correct and enhancement features would involve several technical components:

  1. Semantic Similarity Engines:

     • Utilize embedding models (like those behind LLMs themselves, e.g., Sentence-BERT, Word2Vec, or even the LLM's internal embeddings) to understand the semantic meaning of the user's prompt.

     • This allows for identifying semantically similar, but better-phrased, alternatives even if the exact words don't match.

  2. Grammar and Spell Checkers:

     • Integrate traditional NLP tools for basic spell checking and grammar correction. This can be done using existing libraries (e.g., NLTK, spaCy, LanguageTool) or fine-tuning smaller models for this specific task.

  3. Prompt Engineering Best Practices Database:

     • A curated database of common prompt patterns and successful modifiers (e.g., "summarize in bullet points," "act as a [persona]," "explain simply") could be developed.

     • When a user types a prompt, the system could suggest adding relevant modifiers from this database based on the prompt's initial intent. For example, if a user asks "Tell me about climate change," the system could suggest "Explain climate change in the style of a scientific report" or "Provide 5 key solutions to climate change."

  4. Generative AI for Prompt Rewriting:

     • A smaller, specialized LLM could be fine-tuned specifically for the task of prompt rewriting and enhancement. Given an initial prompt, this model could generate several clearer, more effective alternatives.

     • This model would need to be trained on a dataset of "bad prompt" -> "good prompt" pairs, perhaps generated programmatically or through human annotation.

  5. User Feedback Loop:

     • Allow users to accept, reject, or further edit suggestions. This feedback can then be used to continuously improve the underlying models and the prompt enhancement database.

  6. Integration with LLM API:

     • The prompt enhancer would sit between the user interface and the main LLM API. Before sending the user's prompt to the LLM, it would analyze and offer suggestions. If the user accepts a suggestion, the modified prompt is then sent.

  By combining these technical approaches, a robust and highly beneficial prompt auto-correct and enhancement system could be developed, revolutionizing how users interact with LLMs.

Real-World Problem

Overflowing dustbins are more than just an eyesore—they create foul smells, attract pests, and spread infections. At home, this means unpleasant chores; in hostels and offices, it affects shared spaces; and in hospitals, it can even compromise patient health. The problem isn’t just the waste itself, but the fact that bins give no signal when they need attention.

Gap in Current Solutions
• Traditional bins provide no indication when they’re full.
• Odours build up before anyone notices.
• Staff waste time checking bins repeatedly.
• Available smart bins are expensive and lack simple, practical features like odor control.

Who Benefits?

• Families → Fresher homes with less cleaning stress.
• Students & Staff → Cleaner, more pleasant hostels and offices.
• Healthcare Workers → Safer, more hygienic wards.
• Communities → Improved waste management at scale.

Why This Matters?

Waste disposal is a routine part of daily life, yet poorly managed bins reduce comfort and hygiene everywhere. If dustbins could actively control odour and signal when they’re full, we’d save time, avoid mess, and keep our surroundings healthier.

Innovative Features
1. Odour Neutralizer → Activated carbon or gel filter to prevent bad smells.
2. Fill-Level Detection → Sensors to track when the bin is nearly full.
3. Smart Alerts → LED indicator or phone notifications for timely disposal.
4. User-Friendly Design → Works like a normal bin, but smarter.

Conclusion

The Smart Dustbin with Odour Control and Alerts makes waste management simple, hygienic, and stress-free. By combining freshness, convenience, and technology, it turns an ordinary bin into an essential tool for cleaner living.

Elderly care and safety at home is one of the growing problems in today's society as many seniors are bound to living alone due to family circumstances. This causes families to constantly worry about accidents and medical emergencies. Solutions such as trackers and panic buttons exist but they are often stigmatized and fail to help in critical moments. That's where SafeNest comes in!

SafeNest is an AI-powered, invisible safety net for seniors. Instead of a wearable gadget, it uses a series of sensors which are mounted on the ceiling. These sensors track movement and even subtle changes in breathing or other vitals. If the system detects something unusual, like signs of distress or prolonged inactivity, it automatically alerts emergency services as well as family members. 

SafeNest is a non-intrusive design, which makes it stand out from other care devices. The seniors don't have to remember to charge it or wear anything. It helps in maintaining their dignity while still ensuring that they're safe. It can also be activated with voice commands. So if a senior says "I need help", SafeNest responds immediately. It is beneficial to a variety of people, like the seniors, their families and even the healthcare systems. 

This problem matters to me because I've seen my grandparents stuggle with living alone due to deteriorating mobility and memory. Watching them hesitating to ask for help makes me realize how dignity often stops them from seeking help. SafeNest ensures that they feel independant while also keeping them safe. 

Technically, the system could use motion sensors like LiDAR, AI chips for local data and cloud based alerts for family and emergency services. Also, SafeNest can easily fit in with the uprising of smart homes.

In conclusion, SafeNest promises safety and dignity to the elders while also reducing the stress of their well-being for their families. 

We’ve all had that moment: you’re hurrying to class, a late-night study session, or an important group project meeting when suddenly you realize you forgot something essential — your phone charger, calculator, or maybe that one HDMI adapter you need to connect your laptop. It’s such a small thing, but it throws your whole plan off. Asking around feels uncomfortable, buying spares is unnecessarily expensive, and casually borrowing from friends doesn’t always work out. Yet these are basic tools almost every student needs at some point, and being without them can be stressful and disruptive.

That’s the gap BorrowBox is designed to fill. Imagine a secure, easy-access locker system on campus stocked with the items students most often forget — phone chargers, scientific calculators, laptop adapters, headphones, and even simple stationery like pens or markers. The idea is intentionally simple: scan a QR code, check out what you need with your student ID, and return it when you’re done. No deposits, no complicated forms, no wasted time.

The value is twofold. First, BorrowBox reduces waste — students won’t need to buy backups for items they rarely use, which means fewer unused gadgets ending up in drawers or eventually in the trash. Second, it relieves that constant low-level stress of being unprepared for class, a test, or a presentation. Because the problem is so common and the solution is so effortless, I believe this is something students would adopt immediately.

The pilot version could be extremely lightweight: just 8–12 items placed in one high-traffic location like outside the library. For the backend, a Google Sheet for tracking, QR code labels on items, and occasional staff checks are more than enough to validate the idea.

Longer term, BorrowBox could scale through partnerships with campus cafés, hostels, or even tech companies that want to sponsor lockers. A low-cost membership fee could make it financially sustainable while keeping access unlimited. To measure success, the focus would be on one key metric: the reliability of returns. If items are consistently checked back in, that’s proof the service is both trusted and useful.

Tagline: Borrow a charger for 2 hours. No deposit, no drama.

Most people think differently about economic health and physical health. But they are really linked to depth: Economic stress affects sleep, mental health and physically good, while poor health often leads to unexpected medical bills, reduction in productivity and loss of income.

Our solution is a smart platform that integrates financial advice with health tracking.

Financial advisory engines: Personal budget, savings and investment recommendations run by AI. It is beneficial for your lifestyle, income and goal-he buys a house, pays a loan or creates long-term money.

Integration of health tracking: Wear with activity, sleep, stress and nutritional monitoring and washing with health apps.

Behavior Insight: The stage links dots between your financial habits and your health trends.

For example:Be aware of the level of high stress during the over -speed period. Suggest a healthy, cost -calculated lifestyle alternative (such as a food plan or a little walk).

Allocation of healthy behavior with financial incentives, for example, every time you meet a fitness mile, automated microbes.

Holistic dashboard: A simple, a place where you look at the health and body health aspects of your money.

Results : Users get control of both the wallet and their goodness. Instead of chasing money on health costs - or vice versa - our platform helps create a balanced, durable lifestyle.