1. Title and Abstract: Clearly state the title of the invention and provide a concise summary of the invention’s key features and benefits.
2. Background and Prior Art: Describe the existing problems or challenges in the field of smart helmets and the technologies currently available. This section provides context for your invention’s novelty.
3. Field of Invention: Define the technical field to which the invention belongs, which in this case is smart helmets with integrated sensors.
4. Summary of the Invention: Briefly outline the invention’s technical features, its purpose, and how it solves existing problems.
5. Detailed Description of the Invention: This is the core of the application and should include:
   • Components and Sensors: Describe in detail the various components and sensors integrated into the helmet. Explain how they work together to provide the helmet’s smart functionalities.
   • Integration Techniques: Detail how the sensors and components are integrated into the helmet. This could include mechanical, electrical, or software integration methods.
   • Data Processing: Explain how the data collected by the sensors is processed, analyzed, and utilized to enhance safety and other functions of the helmet.
   • Connectivity: Describe any wireless communication methods used to transmit data from the helmet to external devices, networks, or cloud platforms.
   • Use Cases: Provide examples of the different use cases your smart helmet addresses, such as industrial safety, outdoor activities, home usage, etc.
   • Processing Units: If applicable, describe any processing units or chips responsible for running algorithms and AI/ML models to enhance the helmet’s capabilities.
6. Advantages and Novelty: Clearly state what sets your invention apart from existing technologies and the advantages it offers.
7. Drawings and Diagrams: Include detailed drawings, diagrams, and schematics of the helmet’s design, sensor placements, and integration methods.
8. Claims: This is one of the most important parts of the patent application. Claims define the legal boundaries of your invention’s protection. They should be specific, clear, and cover all novel aspects of the invention.
9. Implementation Examples: Offer practical examples of how the smart helmet could be used in various scenarios. This helps illustrate the potential applications of your invention.
10. Technical Details: Provide specific technical details, such as sensor specifications, data processing algorithms, connectivity protocols, etc.
11. Supporting Data: If available, include experimental data, test results, or simulations that demonstrate the effectiveness and functionality of the smart helmet.
12. References: List any references to prior patents, scientific literature, or other documents that are relevant to your invention.

1. Title and Abstract:

“Integrated Additively Manufactured Smart Helmets with Multi-Use Applications”

The present invention relates to an innovative integrated additively manufactured smart helmets that revolutionizes traditional helmet concepts. Developed by Numorpho Cybernetic Systems, the helmet utilizes parametric modeling, generative design and seamlessly integrates sensors and advanced technologies. This technology, referred to as Project Tiramisu, encompasses the CONNECT-DETECT-PROTECT framework, elevating the helmets’ capabilities beyond mere physical protection.

The smart helmets are equipped with a range of sensors including those from Arduino’s Nicla family (Sense ME, Vision, and Voice), enabling diverse applications. These applications span industrial safety, construction, outdoor activities, home monitoring in well care facilities, first responder scenarios, military deployment, and more. The integrated sensors, data processing algorithms, and AI-driven features transform the helmets into intelligent devices capable of real-time environmental analysis, predictive behavior modeling, and responsive alert systems.

This patent application elucidates the design, functionality, and technical details of this integrated sensor system, outlining its novel contributions to the fields of helmet safety and wearable technology.

2. Background and Prior Art:

All current helmets suffer from the same problem – bulky packaging adds to transportation costs, warehousing space and environmental waste.

Our folding helmet is a collapsible, 3D printed helmet that revolutionizes the way people ship, store, and carry helmets. When transporting, 6 folded Armadillo Helmets can fit in the same space it would take to package a single traditional helmet enabling significant savings due to its smaller footprint.

This helmet is our testament to Additive Manufacturing, and it personifies our “Born not Built” philosophy to create transformational products and services. With the same or better safety guarantee as other helmets in the market at a fraction of the form factor, the Armadillo Helmet is set to make a serious shift in the protective headgear market.

As part of our projects in the micro-mobility space, a helmet that would neatly fold into a form factor that could be easily carried around will be our first product to establish this new sense of freedom and mobility after having been constrained in movement due to the COVID pandemic. The foldability aspect of the helmet would facilitate:

• Shipment – Ship more helmets in the same volume.
• Warehouse storage space – Storage space is reduced.
• Usability aspect – Easily fold the helmet to make it less clunky for carrying it around.

The prime directive of this project is to achieve the minimal optimized shape goals of foldability that adhere to compliance requirements. Parametric modeling is a theme that runs across the spine of this project. Additionally, being customizable and 3D printed using Additive Manufacturing technologies will mitigate supply chain issues and make it more customer centric in function.

3. Field of Invention:

In this project we utilize the tenets in CAD, CAE and Additive Manufacturing – Parametric Modeling, Simulations, Generative Design, 3D-printing, purposeful use of Materials and Design for Manufacturability accomplish what we term “Born not Built”.

4. Summary of the Invention:

The present invention introduces a groundbreaking additive manufacturing and fully customizable helmet based on head shape variations with integrated sensor system for safety and event monitoring, reshaping conventional helmet paradigms. Developed by Numorpho Cybernetic Systems, this innovation, known as Project Tiramisu, seamlessly integrates advanced sensors into foldable helmets.

The invention’s core lies in the CONNECT-DETECT-PROTECT framework, which transcends traditional helmet functionalities. By incorporating sensors like those from Arduino’s Nicla family (Sense ME, Vision, and Voice), the smart helmets cater to a spectrum of applications including industrial safety, construction, outdoor pursuits, home monitoring, emergency response, military operations, and more.

These integrated sensors, coupled with sophisticated data processing algorithms and AI capabilities, empower the helmets to analyze their surroundings in real time, predict user behavior, and trigger responsive alerts.

This summary outlines the invention’s pivotal role in elevating helmet safety and wearables to new dimensions, detailing its technical intricacies and trailblazing contributions.

5. Detailed Description of the Invention

We used anthropometric data gathered during the 2003 NIOSH survey, parameters for new head-forms in five size categories were developed by the National Personal Protective Technology Laboratory (NPPTL) of NIOSH.

Shown below are three-dimensional (3D) scans of five individuals, who most closely represented a given size category were averaged together.

Five distinct sizes (small, medium, large, long/narrow, and short/wide) of digital 3D head-forms have been created to account for the overall size and shape of the face. The NIOSH head-forms are symmetric and represent the facial size and shape distribution of current U.S. respirator users.

6. Use Cases:

A summary of the use cases is detailed below

1. Industrial Worker Safety: The smart helmets equipped with integrated sensors can play a pivotal role in enhancing industrial worker safety. By monitoring parameters like temperature, gas emissions, and physical movement, the helmets can detect potential hazards in real time. The AI algorithms can analyze data patterns to predict unsafe conditions, triggering alerts and ensuring prompt preventive actions.
2. Smart Monitoring for Manufacturing: This comprehensive solution covers the entire lifecycle of factory assets. The smart helmets, in this context, can aid in provisioning and commissioning of equipment, tracking their performance, and predicting maintenance needs. This minimizes downtime, optimizes workflows, and contributes to overall operational efficiency.
3. Open Space Monitoring in Construction Sites: In construction sites, where workers often operate at varying elevations, the smart helmets’ sensors can detect proximity to edges and potential fall risks. The helmets can provide warnings to workers and supervisors, helping prevent accidents and injuries.
4. Closed Space Monitoring in Mines: Underground mines are prone to toxic gas emissions. Smart helmets equipped with gas detection sensors can continuously monitor air quality. In case of hazardous gas levels, the helmets can alert miners and supervisors, enabling swift evacuation and safety measures.
5. Monitoring Imbalance Conditions in Nursing Homes: In nursing homes, smart helmets can serve as an invaluable tool for resident safety. The helmets can detect sudden falls or imbalance conditions, instantly alerting caregivers. Additionally, the helmets can continuously monitor residents’ well-being, tracking vital signs and issuing alerts in case of anomalies.
6. First Responder Scenarios: During emergency responses, smart helmets worn by first responders can gather and transmit critical data. By combining geospatial information with helmet data, incident commanders can make informed decisions. For instance, in a fire scenario, the helmets can monitor temperature, smoke levels, and oxygen concentration, aiding firefighters’ safety and effectiveness.
7. Outdoor Recreation Safety: Beyond industrial and workplace contexts, the helmets can enhance safety during outdoor activities like biking and rollerblading. They can detect sudden impacts and provide real-time feedback to users. Additionally, the helmets can communicate with navigation apps, ensuring safe routes and geolocation data.
8. Sports and Athletics: In sports and athletic training, smart helmets can monitor athletes’ performance metrics such as heart rate, head impacts, and body movement. Coaches and medical staff can analyze this data to optimize training routines and prevent injuries.
9. Automotive Industry: In automotive manufacturing, the helmets can aid in assembly line tasks. Sensors can guide workers through complex processes, ensuring correct component placement and reducing errors.
10. Search and Rescue Operations: During search and rescue missions, the helmets’ geospatial integration can facilitate coordination among team members. Sensors can also help locate survivors in difficult terrains, providing a lifeline in critical situations.
11. Construction Equipment Operation: Helmets can be extended to operators of heavy machinery in construction sites. Sensors can monitor operator fatigue levels and ensure adherence to safety protocols, reducing the risk of accidents.
12. Healthcare Support: Apart from nursing homes, smart helmets can assist in hospital settings by monitoring patients’ vital signs, providing real-time updates to medical staff, and alerting them to any sudden changes.

These use cases highlight the versatility of our smart helmet technology, showcasing its potential to revolutionize safety, communication, and monitoring across various industries and scenarios. Each application demonstrates the helmets’ capacity to not only prevent harm but also provide valuable data-driven insights.

7. Claims:

Below are some potential claims based on the information provided:

1. A smart helmet comprising:
   • a folding structure,
   • an integrated sensor system including sensors from Arduino’s Nicla family,
   • a data processing unit for real-time analysis of sensor data,
   • wireless communication capabilities for transmitting data to external devices, and
   • AI-driven algorithms for predictive behavior modeling.
2. The smart helmet of claim 1, wherein the integrated sensor system includes Sense ME, Vision, and Voice sensors from Arduino’s Nicla family.
3. The smart helmet of claim 1, further comprising a communication module for establishing connectivity with external networks or cloud platforms.
4. A method for enhancing helmet safety and functionality, comprising:
   • integrating sensors into a folding helmet,
   • processing sensor data in real time,
   • predicting user behavior using AI-driven algorithms,
   • transmitting data to external devices wirelessly, and
   • generating responsive alerts based on sensor data analysis.
5. The method of claim 4, wherein the integrated sensors include environmental sensors, motion sensors, and audio sensors.
6. The method of claim 4, further comprising coordinating helmet functionality with external IoT systems for synchronized operations.
7. A wearable device for industrial safety comprising:
   • a folding helmet with integrated sensors,
   • a data processing unit for continuous analysis of sensor inputs,
   • predictive modeling algorithms for user behavior,
   • communication means for transmitting data to centralized systems, and
   • an alert system for immediate response to hazardous conditions.
8. The wearable device of claim 7, wherein the integrated sensors include gas detection sensors, thermal sensors, and impact sensors.
9. The wearable device of claim 7, further comprising a display module for providing real-time feedback to the user.
10. A system for intelligent environmental monitoring, comprising:
    • a smart helmet incorporating environmental sensors,
    • data processing components for analyzing sensor data,
    • AI algorithms for forecasting environmental trends, and
    • communication modules for relaying analyzed data to remote monitoring stations.
11. The system of claim 10, wherein the environmental sensors include air quality sensors, temperature sensors, and humidity sensors.
12. The system of claim 10, further comprising an adaptive learning mechanism for refining predictive models based on historical sensor data.

8. Implementation Examples:

We have Industrial Worker Safety as our first implementation example and are also creating a holistic Smart Monitoring for Manufacturing that deals with the complete activities for Provisioning, Commissioning and Mobilization of assets in a factory floor. Other than this we are looking for open space monitoring in Construction sites where elevation is a key issues and closed space monitoring in Mines where toxic gas emissions might be an issue. We are also looking at monitoring imbalance conditions and wellbeing in nursing homes where the smart helmets could not only provide alerts during a “person down situation” but also send alerts to the concerned authorities. Another use case could be a first responder scenario where it could correspond with geospatial data.

9. References:

1. Google’s Smart Helmet Patent: Google has filed patents related to smart helmets, especially in the context of augmented reality (AR) and head-mounted displays. These patents might have insights into integrating technology into helmet designs.
2. Sensor Integration and Wearable Safety Gear Patents: Search for patents related to sensor integration into wearable safety gear, such as helmets and vests. These patents might provide insights into how sensors are integrated, data processing methods, and safety features.
3. IoT and Wearable Technology Patents: Explore patents in the broader field of IoT and wearable technology. While not specific to helmets, these patents might offer innovative approaches to sensor integration, data communication, and AI/ML algorithms.
4. Occupational Safety and Industrial Wearables Patents: Look into patents related to occupational safety and industrial wearables. These patents could offer insights into how sensors are used to enhance safety in industrial settings.
5. Augmented Reality (AR) Helmets: AR helmets often incorporate sensors for both safety and immersive experiences. Patents in this area might provide ideas on how to integrate sensors into helmets.

Part of what we are doing with the smart helmet is instituting a data engineering stream where in data ingested will be stored and processed in different layers – at the device, at the edge, in a coordinated fog region or on the cloud. This will include the appropriate data transfer along with security and privacy considerations that will need to be implemented at every transfer node so that we are compliant with all protocol needs. For this we will be working with our partners in integration in what we called a Lined Solutioning methodology where we will modularly include their tool/service into our provisioning ecosystem. What should we be mindful of when we do this from an IP perspective?

When implementing a data engineering stream with partners and integrating their tools/services into your smart helmet ecosystem, there are several important considerations from an intellectual property (IP) perspective. Here’s what you should be mindful of:

1. Confidentiality and Non-Disclosure Agreements (NDAs): Prior to sharing any sensitive information with your partners, ensure that you have well-drafted NDAs in place. This will legally bind them to keep your proprietary information confidential and prevent them from using it for their own purposes.
2. Ownership of IP: Clearly define the ownership of intellectual property that results from the collaboration. This includes any jointly developed technologies, algorithms, or solutions. Establish whether the IP will be jointly owned, owned by one party, or if rights are shared in specific contexts.
3. Licensing and Usage Rights: If your collaboration involves using each other’s technologies or services, outline the terms of usage in a licensing agreement. Specify how your partners can use your technology and how you can use theirs. This should cover the scope, duration, and any payment arrangements.
4. Data Handling and Privacy: Given that you’ll be dealing with data transfer and storage, address privacy and data protection concerns. Clearly define how personal data will be handled, who is responsible for data security, and how compliance with relevant regulations (like GDPR) will be ensured.
5. Security Measures: Ensure that security measures are established and agreed upon for data transfer at different layers. This includes encryption protocols, access controls, and any authentication mechanisms.
6. Protocol and Standards Compliance: Depending on the industries you’re operating in, there might be specific protocols and standards that need to be adhered to. Ensure that your integrated solutions are compliant with these standards to avoid any IP infringement issues.
7. Documentation: Keep detailed records of the collaboration process, including discussions, decisions, and agreements made. This documentation could be crucial in case of any future disputes over IP ownership or usage.
8. Patent Filings and Protection: If your collaboration leads to innovations that are patentable, consider how you want to handle patent filings. This could involve filing jointly, individually, or cross-licensing.
9. Termination Clause: Have a clear termination clause in your collaboration agreement. This should outline the steps to be taken in case either party decides to end the collaboration, including how to handle ongoing IP usage.
10. Jurisdiction and Governing Law: Clearly state which jurisdiction’s laws will govern any potential disputes. This can be important if you and your partners are located in different countries.
11. Legal Counsel: Given the complexity of IP issues, it’s wise to involve legal counsel with expertise in IP and technology law to help you draft comprehensive agreements that protect your interests.

Remember that every collaboration is unique, so the agreements and considerations might vary. It’s crucial to customize your agreements to reflect the specifics of your partnership and to ensure that all parties are on the same page regarding IP rights, usage, and compliance.

NITIN UCHIL – Founder, CEO & Technical Evangelist
nitin.uchil@numorpho.com

Examples of Patent Applications

• NUMORPHO’s Smart Helmet Patent Application
• Example 1
• Example 2