LUGGAGE SYSTEM AND TRAVEL ACCESSORIES

Abstract

The invention relates to an AI-powered smart luggage system integrates multiple advanced features to enhance user convenience and security. It consists of a luggage body equipped with RFID sensors for real-time tracking of packed items, a weight sensor to monitor total luggage weight, and proximity sensors for detecting unauthorized access. A biometric lock secures the luggage, while a power supply supports all electronic components. The system's processor executes AI-based algorithms to generate personalized packing recommendations and provide weight management suggestions via a mobile application. It also triggers alerts in case of security breaches. Additional features include QR codes for lost luggage recovery, a USB charging port, and an augmented reality interface for efficient packing visualization. The system learns from user behavior to improve recommendations and supports voice control and third-party app integration. This platform offers a seamless travel experience with sustainability tracking and community-based travel tips.

Specification

Description:An AI-powered smart luggage system (100) that integrates advanced technologies like RFID sensors 102, biometric locks, AI-driven recommendations, and proximity alerts in the AI-powered smart luggage system (100) changes the way things are managed while incorporating security into the management of one's baggage. Its mobile application provides an interactive interface with the luggage and has given the travellers an experience stress-free and seamless travel.

The luggage body 101 is the physical structure that holds within all sensors and electronic parts and is designed to be very tough and ergonomically convenient. RFID sensors 102 are inserted in every compartment of the luggage for instant tracking of anything packed in individual items in real time. A user is able to check and track his and her luggage to ensure nothing is forgotten.

A weight sensor (103) at the bottom of the luggage is also continuously weighing the total weight during packing. It provides suggestions about the weight management of the packing that reaches the limits of the airlines. Proximity sensors (104) are integrated along with all the sides to make sure nothing inappropriate happens to it from any unauthorized entry or manipulation. It gets triggered, it sends real-time security alerts in case someone tampers with it to ensure the belongings are safe.

The system has a biometric lock 105 that opens the door only through fingerprint recognition. The door does not have any traditional keys or passwords. These components are powered by the power supply 106; apart from the power supply 106 of electronic features is integrated with the luggage, it also has a USB charging port for external devices. The processor (107) controls the system, which interfaces with all sensors and locks, and internal memory that stores instructions and learns about user data to improve recommendations over time.

The AI-powered smart luggage system 100 provides the user with personalized packing recommendations based on his or her traveling data and the user's personal profile through a mobile application. It uses the assessment of such data to suggest the best lists for each trip. While the user packs, RFID sensors 102 detect the presence of each item, thus enabling travellers to track their belongings, reducing the likelihood of leaving something behind.

The integration of the weight sensor allows real-time monitoring of the system. It sends alerts from the system if the luggage exceeds a predefined limit; it advise trimming down extra baggage to avoid additional cost. Proximity sensors are used by the system to avoid unauthorized movement. If the luggage has been left alone, then the system send an alert immediately to the user through the mobile application the moment the system detects any unauthorized movements or somebody has accessed it.

The biometric lock 105 allows travellers to lock and unlock luggage safely through fingerprint recognition, providing both convenience and enhanced security. Users have full management of the luggage system through mobile applications and remotely check the contents, lock status, and weight.

The AI-based smart luggage system is in a constant learning process by finding out the trends of users and their travel patterns to enhance recommendations made to the user. With each and every trip, the system analyzes the travel data for improving packing suggestions on future journeys so that the most relevant items appear in subsequent journeys. After a certain period the system predict the needs of the users much better.

Among the new features introduced in the system are the AR interface provided by the mobile app, allowing the traveller to visualize the contents of his luggage and optimize the packing space with more effectiveness. Aiding convenience further, the system has also encouraged sustainable travel by tracking the environmental impact of packing habits and providing eco-friendly suggestions.

The AI-powered smart luggage system 100 comes with an extra QR code on the outside that connects to one's account, so in case of a loss, easy retrieval is made possible. The traveling individual is also able to use voice control functionalities, thus enjoying hands-free interaction with the luggage system. Additionally, the app is able to connect the individual to a community of other travellers, a step that helps in amplifying the exchange of knowledge as the user engage fellows on how they best pack up and where to visit.

This system increase flexibility by being API-friendly and, therefore, easily integrating into third-party services. Thus, a luggage system becomes just one constituent part of a travel ecosystem that might connect to applications tracking flights, booking hotels, and ordering transportation. Connectedness with external services ensures that users get better experience their travel product through integrated everyday aspects.

The system has further added a USB charging port for charging up the smartphones and all other devices through the power supply in the luggage. This feature is sure to make travelers connect throughout their journey and be powered up.

The AI-powered smart luggage system 100 begins its operation by taking user profile details as well as travel information through the mobile application, which the AI engine in the system will read and analyze to provide customized packing recommendations for the type of trip. Once items start getting added to the luggage, RFID sensors 102 detect and register each item so that users are able to see the contents in real time through the mobile app.

The integrated weight sensor also monitors the actual total weight of the luggage during the whole process of packing it. Once the weight approaches the limit, the system alerts the user with different types of weight management alerts, providing recommendations regarding methods of reducing the load. After packing the luggage, users can protect it by using the biometric lock 105 in order to allow only authorized individuals to open the luggage.

While traveling, the proximity sensors scan the bags and monitor for any unauthorized access. In such an attempt of unauthorized access, it alerts the user of this incident with a message through the mobile application. After each trip, it analyzes post-travel data to improve future suggestions on packing with continuous improvement in its suggestions.

1. Embodiments:
Luggage body 101:
The smart luggage system is based on a high-strength polycarbonate lightweight frame, able to resist impacts and environmental influences without sacrificing the low weight of the total structure. The luggage body is designed according to standard airline size regulations for carry-on luggage. There are several sections in the inside of the luggage, used for various purposes. These sections are prepared to make maximum use of available space and to assist in keeping items organized and easily accessible.

RFID Sensors 102:
There are a number of RFID sensors 102 placed inside the luggage body. Such sensors detect the availability of RFID tags attached to the items kept inside the luggage and inform about the items in real time.

Weight Sensors:
High-precision weight sensors are integrated into the base of the luggage. These continuously measure the weight of the luggage and any contents inside, thus giving real time weight information.

Proximity Sensors:
A set of proximity sensors are embedded along the periphery of the luggage, which will detect movement and possibly tampering attempts when the luggage remains unattended.

Biometric Lock 105:
There is an equipping of the luggage with a fingerprint scanner on the locking mechanism. With this aspect, the biometric lock will only allow authorized people to open the luggage; hence providing confidentiality and security for its contents.

Key-Based Lock:
There is also a traditional key-based lock incorporated as another way of accessing it in case the electronic devices fail.

Power Supply 106:
All electronics for this luggage are led by a rechargeable lithium-ion battery that will have a long cycle life and can be easily recharged from a USB-C port.

USB Charging Port:
The user will be able to charge devices from the battery in the luggage through an external USB-A port.
The exterior of the luggage has a QR code unique to it, linked to the account of the user, so that it may be easily recovered if the bag is lost.

LED Status Lights:
A set of LED lights present along the edge of the luggage indicate low battery, if the state of lock and whether one is approaching or passing the bag

2. Software and AI
Mobile App:
The central interface to use with the smart luggage system is a user-friendly mobile application for both iOS and Android platforms, covering all features and controls.

AI Engine:
The core functionality of this smart luggage system operates on an advanced AI engine that takes into consideration processed relevant user data, information about the travel, and historical patterns in making recommendations and alerts to the users in return.

Machine Learning Algorithms:
The system employs machine learning algorithms that continually learn from user behaviors and traveling patterns as well as improving the accuracy of recommendations over time.

Cloud Integration:
Cloud is utilized in storing and processing user data as well as luggage information so that the device will always be backed up, and users will be able to retrieve and synchronize their features smoothly across various devices.

3. Features and Functionalities:
Registration of User and User Profile Creation:
The users begin by downloading the app and creating a profile. Creating the profile requires the users to enter all the details themselves, such as age, gender, and personal traveling habits, which becomes the foundation for offering personal recommendations.

Pre-Travel Preparation:
The users input travel details into the app like destination, number of days, business/leisure purpose, and specific activities before starting a journey that helps the app deliver the right recommendations.

Packing Support:
Leveraging the user profile and travel information, the AI engine generates a customized list of what to pack. These would include the right weather at the destination, the type of activities planned, and personal user preferences.

Smart Suggested Packs:
Once people start packing their luggage, the system can scan RFID tags on each item using a mobile app. The system will provide users with real-time feedback that lets them know if the items needed for the trip are packed and suggests alternative or supplementary options based on the user's history and their travel plans.

Real Time Item Tracking:
Once items are put into the luggage, their positions in the baggage continue to be monitored by RFID sensors. It creates a visualization of packed items even while keeping the luggage closed through the mobile app.

Retrieval of Items
When an item is required to be located inside a baggage on being packed, the application helps locate the exact location in which the product is placed and enables quick retrieval of the item with ease.

Monitoring Weight:
The weight sensors provide real-time information about the total weight of the luggage. This information is thus presented in the application to enable users to monitor the contents of their packing so that they do not exceed the limit set by the airlines.

Weight Distribution Suggestions:
If the luggage weight approaches airline limit, this system suggests removing and redistributing some of these items. It ranks the item based on its importance-a score coming from usage history and predicated on travel context, and includes alternative items that can substitute in making informed decisions about what to pack or remove.

Biometric Security:
For the biometric padlock, users can add several fingerprints - their own and from trusted individuals. The fingerprint reader will only grant access to authenticated individuals.

Proximity Alerts:
Proximity sensors are activated once the luggage gets disconnected from the user's smartphone, meaning it has been left behind. They alert the person directly with a mobile device in case of unwanted movement or attempts at tampering.

Location Tracking:
If there's a need to separate the luggage from its owner, the last known location is recorded too, based on the last connection of the smartphone of the user. It could be pretty beneficial for recovering lost luggage.

QR Code Recovery:
If the luggage gets lost, someone else can scan the QR code using any smartphone camera. It will generate basic contact information on how the luggage could be returned to its owner without compromising the privacy of the owner.

Battery Management:
The app displays actual real time battery levels of the luggage. It will monitor the actual real-time state of the battery and send alerts when the battery level is low, estimating a likely duration of usage in consumption patterns.

Travel Information Hub:
The smart phone app would be considered as one single source for all kinds of related travel information. It would allow digital copies of travel documents, display real time data of flights and even destination-specific tips and recommendations.

Historical Data Analysis:
These habits in packing, usage of items, and travel patterns are monitored over time. The insights from these metrics feed the predictors that progressively give even more accurate and pertinent suggestions for future trips.

4.System Operation and User Interaction
Pre-Trip Phase
The user opens the mobile app, types in the details of their trip, and gets back an output from the AI engine processed with the details of the user profile and historical details regarding a personalized list of things to pack.

Packing Process:
Once the user is done packing, the smartphone reader reads each item RFID tag. The application checks whether the item exists in the packing list and suggests adding missing essentials during packing. Weight is monitored while packing and displayed via the application.

Security Lock on Baggage:
When the user closes the luggage, the biometric lock of the baggage is activated. They can add or remove fingerprints to unlock the baggage using the application whenever needed.

Transit Tracking:
The user can, therefore, check on the status of his or her luggage anytime even when traveling. One can, thus, get a list of items that have been packed up, obtain the present weight, and get any alert from security issues.

Retrieval of Items:
If one needs to find a particular item, he or she can use the app to find the particular item within the luggage. The app gives him visual information concerning the location of the item hence quickly retrieving it.
If checked baggage is moved or tampered with when unattended, the user will receive an instant alert on their mobile phone to take immediate action.

Lost Baggage Recovery:
If the luggage is lost, the user may report its loss through the app. If somebody finds the luggage and scans the QR code attached to it, they get every detail of contact to return it back to its owner.

Post-Travel Analysis:
The system will analyze the user's packing for all successful journeys by providing information about the constraints, cost, and weather. Travel information so that it can update its proposal in the subsequent visits. The user can also comment via the app to have the system improve even further.

5. Technical Execution:
RFID Technology:
The system use passive RFID tag operating in the Ultra High Frequency (UHF) band at the 860-960 MHz. These tags are low in size and price with no power source, thus ideal to track individual article within the luggage.
RFID Reader:
RFID readers are mounted at various locations inside the luggage. This covers most of the areas that the RFID will need to do its task by emitting radio waves and powering/communicating with the RFID tags in order to track the luggage item in real-time.

Weight Sensor Technology:
The luggage is designed with calibrated precision strain gauge load cells to ensure accurate weight measurement. The sensitivity is within 0.1 kg or even better for meeting the airline regulations, of course.

Implementation of Proximity Sensors:
This detection system uses a combination of infrared and ultrasonic sensors. A dual-technology system, such as this one, minimizes false alarms while accurately detecting both movement and attempts at tampering.

Biometric Lock Mechanism:
The fingerprint scanner uses capacitive sensing technology and captures an accurate digital impression of the fingerprint based on the electrical charges of the ridges and valleys. The level of security is high and comes with resistance to spoofing attempts.

Power Management:
In addition, the system includes an intelligent module of power management to efficiently utilize a battery pack. The functions "not-counted" are disabled automatically whenever they are in a dormant state and are not being utilized to extend the maximum life of the battery.

Data Encryption:
All interaction between the luggage, mobile application, and cloud servers is encrypted. The usage of AES-256 encryption ensures the user data and travel information is well protected and private.

AI and Machine Learning Framework:
The AI engine is based on a deep learning framework, using neural networks to conduct pattern recognition and decision making. Supervised as well as unsupervised learning techniques are used to improve performance.

6. Manufacturing and Assembly:
Luggage Shell Manufacture:
Use of injection molding techniques to make polycarbonate shells provides consistent quality and strength with cavity-designed mounting points specifically developed for inner components.

Electronic Component Assembly:
The entire part is based on a modular frame, where sensors, locks, and circuit boards are mounted. It's held inside the luggage shell securely in an easy to service and upgrade manner.

RFID Tag Application:
One set of reusable RFID tags per luggage is supplied. Tags are equipped with adhesive backing for garments. For larger items, loop attachments are used.
Every luggage unit undergoes rigorous testingincluding drops, water resistance tests, and electronic component checkswith the objective of determining durability and functionality.

7. Improved User Experience:
Voice Command Functionality:
The smartphone app features voice control in the program. Users can have a hands-free interaction with their luggage by having inquiries on where their items are, checking weight, or being informed on how to pack through voice commands.

Augmented Reality Interface:
This feature of AR within the mobile application comes as an option to view the contents in one's luggage through smartphone cameras. This shows a simple manner in which the location of misplaced items can be tracked and the usage of luggage packs optimized.

Travel Community:
The app is equipped with the functionality that allows users to interact with the travel community at large. This is achieved by means of sharing advice on packing, destination recommendations, and experiences relating to the usage of luggage, thereby enriching the ecosystems of travels.

Sustainability Tracking:
The system tracks how the user's travel and packaging behavior impact the environment. It makes recommendations for greener choices and calculates carbon footprints for every trip, so you have every reason to travel sustainably.

8. Future Expandability:
Modular Design:
The luggage comes with a future-proof design. The internal electronic components are designed to be modular which can be upgraded or even new features can be added without necessarily replacing the luggage itself.

API Integration:
Moreover, the platform comes with an API that helps third-party developers develop compatible applications and services that enrich the ecosystem of the smart luggage platform.

IoT Connectivity:
Compatibility with future Internet of Things networks would make it track a piece of luggage in much more detail and integrate into the infrastructure of a smart city.

This highly detailed description of the AI-Powered Smart Luggage System gives a comprehensive view regarding the main features of this futuristic travel solution, highlighting how this system innovatively attacks everyday travel issues by combining advanced technology with user-centric design, making this invention a significant novelty in the category of travel accessories.

Method of performing the invention
The AI-Powered Smart Luggage System 100 is by taking the following steps to make it reach its full potential and extract all the value out of it:

Preliminary Installation:
- Download the mobile app and register, including personal details and travel preferences.
-Include biometric lock fingerprints for trusted members, if user needs to use this feature
-Take RFID tags dispensed by attaching them to items that frequently pack

Travel Planning before:
All travel plans will need to be entered into the app, from destination, duration of the stay, and purpose of the visit.
Simply view and edit the AI-generated packing list.
Scan each item as it is scanned in to the system utilizing the mobile application on its respective RFID.
View real-time weight updates. Suggestions for weight management are given instantaneously if overloading has been done with Optimize use of space in the luggage through AR.

Security Setup:
Lock the luggage using the biometric lock after scanning in all items.
Set proximity alerts with the application if leaving luggage unattended.

While Traveling:
-Use the app to scan for security alerts and notifications.
-Search for specific lost items of luggage.
-Use the USB charging port on transit while charging electronic devices.

Lost Luggage Situation:
-Report it lost in the app.
Distribute information to the appropriate agencies on the unique QR code details so as to help in retrieving it.

After journey (Post Journey):
- View trip summary in the app, see complete efficiency data on everything packed, as well as item usage data.
- System performance feedback to help future improvement in recommendations.
, Claims:1. An AI-powered smart luggage system 100 comprising:
a luggage body 101;
a plurality of RFID sensors 102 disposed within said luggage body 101;
one weight sensor 103 integrated into the base of said luggage body 101;
proximity sensors 104 embedded around the perimeter of said luggage body 101;
a biometric lock 105 integrated into said luggage body 101;
a power supply 106 used to power electronic components of the system 100;
a processor 107 operatively connected to said sensors and lock;
a memory storing instructions that, when executed by the processor 107, cause the system 100 to:
generate personalized packing recommendations based on user data and travel information;
track locations of items within the luggage in real-time using RFID technology;
monitor total weight of the luggage and provide weight management suggestions;
detect unauthorized access attempts and generate security alerts;
and a mobile application used to interface with said system 100 for allowing users to access and control system features.

2. A method for operating an AI-powered smart luggage system 100 as claimed in claim 1, comprising:
receiving user profile data and travel information through a mobile application;
generating, using an AI engine, a personalized packing list based on said user profile data and travel information;
detecting, using RFID sensors 102, items placed within a luggage body as they are packed;
tracking, in real-time, locations of said items within the luggage body 101;
monitoring, using one weight sensor 103, total weight of the luggage as items are added;
providing weight management suggestions when said total weight approaches a predefined limit;
securing the luggage using a biometric lock;
detecting, using proximity sensors, unauthorized access attempts when luggage left unattended;
generating security alerts in response to detected unauthorized access attempts; and
and providing, through said mobile application, a user interface for accessing and controlling features of the smart luggage system.

3. The system as claimed in claim 1, wherein a memory further stores instructions to learn from user behavior and travel patterns to continuously improve accuracy of packing recommendations and alerts.
4. The system claimed in claim 1, further comprising a QR code affixed to the exterior of the luggage body, said QR code linked to user account information to facilitate lost luggage recovery.
5. The system claimed in claim 1, wherein the mobile application includes an augmented reality interface for visualizing contents and optimizing packing space within the luggage.
6. The method claimed in claim 2, further comprising analyzing post-travel data to refine future packing recommendations and travel suggestions.
7. The system claimed in claim 1, further comprising a USB charging port configured to allow charging of external devices using the system's power supply.
8. The method claimed in claim 2, further comprising providing voice control functionality for hands-free interaction with the smart luggage system.
9. The system claimed in claim 1, wherein the processor is further used to calculate and track environmental impact of user's travel and packing habits, and provides suggestions for more sustainable choices.
10. The method claimed in claim 2, further comprising integrating with a community of travellers through the mobile application to share packing tips and travel recommendations.

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