There is a growing concern of camera hacks, data insecurity, identity faking, and risked privacy in modern security cameras. AdaLens uses Cardano-powered hybrid cameras to solve these issues.
Revolutionizing surveillance with AdaLens: A Cardano-powered AI camera combining neuromorphic intelligence and privacy capabilities for unparalleled identity management, security, privacy and control.
This is the total amount allocated to AdaLens: A Next-Generation Cardano-Powered AI Camera with Neuromorphic Intelligence and Privacy Capabilities.
Sam Jeff
To implement the proposed AdaLens project, we are dependent on established neuromorphic camera manufacturing companies like Prophesee, iniVation, or CelePixel. These companies provide the necessary hardware components. The successful execution of the project relies on the availability and timely supply of neuromorphic cameras from the selected manufacturer. Delays in the manufacturing or supply chain processes could impact the project timeline but this has been factored into the project timeline based on the main proposer's previous experience dealing with these companies. We will ensure that we have the necessary licenses and permissions to utilize any third-party software or technologies required for the project. This includes complying with licensing agreements and ensuring legal usage of proprietary software.
The AdaLens project will not be fully open source. While we value the principles of open source, certain aspects of the project, including proprietary algorithms, firmware, and hardware specifications, will not be publicly available. This is necessary to protect intellectual property rights and maintain a competitive advantage in the market. However, we are committed to sharing relevant documentation, technical specifications, and providing transparency in the implementation and integration of Cardano blockchain technology with the neuromorphic camera system. The goal is to foster collaboration and knowledge sharing within the Cardano community while balancing the need for innovation and commercial viability.
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Our proposed solution, AdaLens, is a next-generation Cardano-powered AI camera that integrates neuromorphic intelligence and privacy capabilities. We have identified the problem of modern security cameras lacking sufficient privacy and data security measures, which often leave users vulnerable to unauthorized access and privacy breaches.
AdaLens aims to address this problem by leveraging the power of the Cardano blockchain to ensure end-to-end encryption and decentralized control over video footage. By combining AI-powered object tracking and classification with event-based and standard cameras, AdaLens offers real-time surveillance with reduced computational and memory requirements. The use of neuromorphic technology allows for efficient processing on low-power embedded platforms, making it suitable for various applications, including mobile nodes and remote security systems. Most importantly, the neuromorphic camera is an automatic motion capture camera and we propose a trigger mechanism for the standard camera to capture HD video, only when there are objects in view. This leads to tremendous reduction in data captured and subsequent storage. Also, the high dynamic range of neuromorphic vision cameras (120 dB vs 60 dB of standard cameras) makes it a natural night vision sensor.
The unique aspect of AdaLens lies in its ability to provide unparalleled control over privacy and data security to users. This is done through decentralized issuance of encryption keys or Atala DIDs. This means that only the user has the key to decrypt their videos, and no one else can access them without their permission. This is a major improvement over traditional surveillance cameras, which are often hacked and have their footage leaked. AdaLens also addresses the growing concern of camera hacking by providing robust security measures to protect data, identity, and privacy. This makes it a more secure alternative to traditional surveillance cameras.
Here are some of the security measures that AdaLens proposes:
AdaLens includes a number of other security features, such as two-factor authentication and facial recognition, to help protect user data. Overall, AdaLens is a more secure and privacy-friendly alternative to traditional surveillance cameras. The beneficiaries of AdaLens are individuals and households seeking enhanced privacy and security in their surveillance systems. By using AdaLens, users regain control over their video footage and have peace of mind knowing that their data is secure and protected from unauthorized access or tampering.
By leveraging Cardano, AdaLens provides enhanced security and privacy. They enable immutable and transparent storage of video data, ensuring its integrity and authenticity. Additionally, AdaLens aims to provide secure access control, allowing authorized parties to securely interact with the camera feeds and recorded footage. Overall, AdaLens provides a robust solution to enhance the trustworthiness, integrity, and privacy of surveillance data, addressing the shortcomings of traditional systems and creating a more secure environment for individuals, organizations, and communities.
Technical Summary:
The benefits of AdaLens to the Cardano ecosystem are multifold. Firstly, it showcases the capabilities and versatility of Cardano's blockchain technology in the realm of Internet of Things (IoT) and home security. This demonstrates the potential of Cardano to be a leading platform for secure and privacy-focused solutions, attracting more users and developers to the ecosystem.
Secondly, AdaLens brings value to the Cardano ecosystem by addressing a key problem faced by modern security cameras. The integration of end-to-end encryption, decentralized control, and neuromorphic intelligence enables users to protect their privacy and data, thereby enhancing the trust and confidence in Cardano's technology.
In terms of impact, AdaLens has the potential to attract users seeking enhanced privacy and security features in their surveillance systems. By providing a unique solution that combines AI-powered object tracking, event-based cameras, and standard cameras, AdaLens offers a compelling proposition for individuals and organizations. This can drive adoption of Cardano's technology and expand the user base of the ecosystem.
While it is challenging to quantify the exact number of users or usage/transactions that AdaLens will achieve within a specific timeframe, we anticipate a gradual growth in adoption as the benefits and features of AdaLens become known to the target audience. We will actively engage with users, gather feedback, and iterate on the solution to ensure its effectiveness and relevance.
Overall, AdaLens not only addresses a significant challenge in the security camera industry but also contributes to the growth and strength of the Cardano ecosystem. It attracts users, showcases the capabilities of Cardano's technology, and reinforces the platform's commitment to privacy, security, and decentralization.
To measure the success of our project, we will utilize a combination of quantitative and qualitative metrics that assess the impact of AdaLens on the Cardano ecosystem. These metrics will enable us to evaluate the benefits, productivity, and growth brought by our innovation in both the short and long term. Some of the key measures we intend to use include:
While quantitative metrics such as adoption rate and partnerships provide numerical indicators of success, qualitative measures such as user feedback and satisfaction offer valuable insights into the perceived value and impact of AdaLens. By combining these metrics, we aim to provide a comprehensive evaluation of the project's success and its contribution to the productivity and growth of the Cardano ecosystem.
By implementing these dissemination strategies, we aim to ensure that the outputs, impact, and opportunities resulting from our completed project are widely shared and accessible. We believe that transparent and collaborative sharing of information is crucial for fostering innovation, attracting new contributors to the Cardano ecosystem, and inspiring future research and development initiatives.
Our team members have a strong background in software development, IoT, blockchain technology, and privacy-focused solutions. We have a deep understanding of the Cardano ecosystem, its principles, and its technical aspects. We value trust and maintain a strong reputation in the Cardano community via successful previous rounds of Catalyst funding.
Our team includes Bharath Ramesh, a leading researcher in the neuromorphic domain, further enhancing our capability to deliver this project with high levels of trust and accountability. He holds a Ph.D. in Computer Engineering with a specialization in AI systems. He has conducted groundbreaking research in the area of event-based cameras and their application in object tracking and classification. His work has been published in reputable scientific journals and presented at international conferences, earning recognition within the academic community.
As a leading researcher in this niche domain, Bharath Ramesh has collaborated with renowned institutions such as National University of Singapore, Nanyang Technological University, and Western Sydney University. He has also worked with industry partners in Singapore to develop innovative solutions for low-power, embedded platforms. He has made significant contributions to the field, as demonstrated by his publications, including:
A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems:
EBBINNOT: A Hardware-Efficient Hybrid Event-Frame Tracker for Stationary Dynamic Vision Sensors:
These publications showcase Bharath's expertise in developing innovative solutions for efficient object tracking and classification using neuromorphic and hardware-efficient approaches. His expertise in designing neuromorphic frameworks for real-time object tracking and classification aligns perfectly with the objectives of our project.
Dr. Bharath Ramesh's presence in our team not only adds significant credibility but also ensures that our proposed solution benefits from the latest advancements and insights in the neuromorphic field. His deep understanding of the underlying technologies and his ability to translate research into practical applications will greatly contribute to the success and impact of our project. We are confident that Dr. Bharath Ramesh's expertise, combined with the collective capabilities of our team, positions us as the best-suited group to deliver this project with the highest levels of trust, accountability, and technical proficiency.
Also, our team has an accomplished blockchain developer in Sam, who has completed several Catalyst projects. And also Robin who worked with us on the FetaChain project, which was funded in the last round. Overall, our actions and interactions reflect our commitment to integrity, professionalism, and ethical conduct. We have built strong relationships with community members and stakeholders, which further strengthens our credibility as a trusted project team.
The main goals for our project are as follows:
To measure the achievement of these goals, we will utilize both quantitative and qualitative metrics. Quantitatively, we will measure the camera's accuracy in object tracking and classification, power consumption levels, and the number of successful transactions on the Cardano blockchain. Qualitatively, we will assess user satisfaction, feedback, and the overall improvement in privacy and data security compared to traditional security cameras.
Regarding the implementation of our approach, we will follow an iterative and agile development process. We will engage in rigorous software development practices, including continuous integration and testing, to ensure the stability and reliability of our software. Additionally, we will establish partnerships with leading neuromorphic camera manufacturing companies, such as Prophesee, iniVation, or CelePixel, to ensure seamless integration of their hardware with our software solution.
Through this approach, we aim to validate the feasibility of our project and deliver a high-quality, Cardano-powered AI camera that addresses the core challenges of privacy, data security, and computational efficiency in the field of video surveillance and security.
Milestone 1: Research and Requirements Gathering
Milestone 2: Hardware and Software Integration
Milestone 3: Privacy and Security Implementation
Milestone 4: Performance Testing and Optimization
Milestone 5: User Experience Enhancement
Milestone 6: Documentation and Knowledge Sharing
The project will be managed using an agile project management approach, with regular sprints and iterations. We will establish a dedicated project team consisting of researchers, developers, and project managers. Communication and coordination will be facilitated through regular team meetings, progress updates, and task tracking. Risks and issues will be identified and addressed promptly to ensure project success and adherence to timelines. Progress will be monitored using project management tools and regular reporting to stakeholders.
The estimated timeline for the overall project is approximately 10 months, considering the duration of each milestone and necessary dependencies. However, it is important to note that the timeline may be subject to adjustments based on unforeseen challenges or changes in project scope.
Milestone 1: Research and Requirements Gathering Deliverables:
Intended Outcomes:
Measurement:
Milestone 2: Hardware and Software Integration Deliverables:
Intended Outcomes:
Measurement:
Milestone 3: Privacy and Security Implementation Deliverables:
Intended Outcomes:
Measurement:
Milestone 4: Performance Testing and Optimization Deliverables:
Intended Outcomes:
Measurement:
Milestone 5: User Experience Enhancement Deliverables:
Intended Outcomes:
Measurement:
Milestone 6: Documentation and Knowledge Sharing Deliverables:
Intended Outcomes:
Measurement:
Budget Breakdown:
Research and Requirements Gathering: $3,000
Hardware and Software Integration: $16,000
Privacy and Security Implementation: $15,000
Performance Testing and Optimization: $10,000
User Experience Enhancement: $8,000
Documentation and Knowledge Sharing: $5,000
Contingency:
Total Project Budget: $63,000 (the equivalent ADA has been requested at current market prices- it is very hard to budget with a volatile commodity so we had to use USD)
Third-Party Products/Services:
Other Funding Sources: If the project cost exceeds the funding request, we will explore additional sources of funding, such as grants, partnerships, or private investments, to cover the remaining expenses.
Note: The budget elements for publicity/marketing/promotion, project management, documentation, and reporting back to the community are included in the respective milestones' costs.
The cost breakdown of the project represents value for money for the Cardano ecosystem in several ways.
Overall, the cost breakdown demonstrates a prudent and strategic approach to resource allocation, providing value for money by ensuring that the project can be executed successfully, delivering tangible outcomes and benefits to the Cardano ecosystem.
Dr. Bharath Ramesh (Project Lead and AI Researcher - Computer Vision Specialist)
Sam Jeffery (Blockchain Expert)
Robin Thomas (and his team of hardware engineers)
Fayaz M (Project Manager)
Additional Team Members (To be recruited)
We have already engaged with the team members and have established direct lines of communication through project management tools and regular meetings. This allows us to collaborate effectively, share progress updates, and address any challenges that may arise during the project.
Please note that consent has been obtained from all team members to include their information in the proposal.