The convergence of artificial intelligence, cryptocurrency, and blockchain has created a communication crisis: professionals must navigate fragmented applications, wallets, agents, and protocols to accomplish what should be a single action. KHALL KII⢠introduces a voice-first communication instrument built natively for the programmable economy. KHALL KII⢠is the consumer-facing communication layer of the KHEMONAUTICS antientropic ecosystem. It combines the Kryptophon⢠language for programmable value, the Khonver⢠universal interoperability protocol, the Khotor⢠computational motor, and the Khounter⢠proof standard into a single, radically simple human interface. The fundamental interaction is Press. Speak. Release. The system understands intent, routes communication, verifies identity, executes authorized actions, preserves memory, and issues cryptographic proof across humans, AI agents, digital assets, and blockchain networks. This paper establishes the complete architecture, product family, vocabulary, hardware tiers, software platform, business model, legal framework, and intellectual property strategy for KHALL KIIâ˘. Every claim is scoped to what is specified and what is designed; implementation status is clearly distinguished from specification status throughout.
Automated Guided Vehicles (AGVs) operating in industrial and critical environments require secure, auditable, and efficient data management. This paper proposes a hybrid architecture that combines ROS/ROS2 robotic middleware, an industrial context platform, and a distributed ledger layer to provide tamper-evident event recording while preserving operational flexibility. A bridging component maps robot states and events into NGSI context entities, which can then be anchored in Hedera Hashgraph or IOTA Shimmer, while a conventional FIWARE/MongoDB deployment is used as an off-chain reference baseline. The proposed architecture is evaluated experimentally using a Raspberry Pi as an AGV emulator under controlled laboratory conditions. Results show that Hedera Hashgraph achieves lower ledger confirmation latency than IOTA Shimmer, with mean DLT-only confirmation times of 4.02 s and 5.01 s, respectively, while the FIWARE/MongoDB baseline provides substantially lower latency (1.52 s) but without immutable auditability. Energy measurements indicate that IOTA exhibits low local device-side energy consumption, though they do not capture the full energy cost of the distributed ledger network. Overall, the study highlights trade-offs among latency, throughput, energy consumption, and auditability in hybrid on-chain/off-chain architectures for industrial AGV systems and provides guidance on ledger selection and deployment design for security-critical industrial applications. Keywords: AGV, DLT, Hashgraph, IOTA, FIWARE, FIROS, IoT, Industrial Robotics, Auditability, Industry, ROS, Industrial Platform
Robots are improving their autonomy with minimal human supervision. However, auditable actions, transparent decision processes, and new human-robot interaction models are still missing requirements to achieve extended robot autonomy. To tackle these challenges, we propose RODEO (RObotic DEcentralized Organization), a blockchain-based framework that integrates trust and accountability mechanisms for robots. This paper formalizes Decentralized Autonomous Organizations (DAOs) for service robots. First, it provides a ROS-ETH bridge between the DAO and the robots. Second, it offers templates that enable organizations (e.g., companies, universities) to integrate service robots into their operations. Third, it provides proof-verification mechanisms that allow robot actions to be auditable. In our experimental setup, a mobile robot was deployed as a trash collector in a lab scenario. The robot collects trash and uses a smart bin to sort and dispose of it correctly. Then, the robot submits a proof of the successful operation and is compensated in DAO tokens. Finally, the robot re-invests the acquired funds to purchase battery charging services. Data collected in a three day experiment show that the robot doubled its income and reinvested funds to extend its operating time. The proof validation times of approximately one minute ensured verifiable task execution, while the accumulated robot income successfully funded up to 88 hours of future autonomous operation. The results of this research give insights about how robots and organizations can coordinate tasks and payments with auditable execution proofs and on-chain settlement.
The smart cities that collaborate with AI-driven autonomous robots are attracting attention for supporting various social activities in the real world. In facilities that provide such services, various systems managing the facility and robots may coexist in the common area. By enabling the systems to interoperate and share information about the status of the facility and robots, it becomes possible to realize a variety of services that support safety and security within the facility. However, while the operators of the facility want to monitor the detailed conditions of the robots, the operators of the robots are cautious about providing the information about the status of robots such as the moving trajectory and various sensor data. To resolve this dilemma, we propose a new system that enables estimation of the operational conditions of the robots by verifying the positions and trajectories at landmarks in the facility without disclosing their internal information. In the proposed system, we focus on the observation of environmental information that accurately reflects the real-world situation for estimating the proximity between the robot and each landmark. As the environmental information, both systems on robots and a facility measure CSI (Channel State Information) and acoustic information. In addition, by utilizing zero-knowledge proof (ZKP) technology, the system for the facility confirms the reliability of the process for estimating the proximity of the robots to the landmark without exchanging detailed internal information. Through the proof-of-concept experiment, applying the proposed system achieved high-accuracy proximity detection with both methods (CSI and acoustic information) yielding precision and recall rates exceeding 0.90.
The real potential of an AI-enhanced and accelerated future lies not just in our collaborative capability but in our ability to go beyond simple collaboration and develop a symbiotic relationship with AI. Because AI is us, our role in this symbiosis is to ensure that we become better human beings that can make AI better. When we are better, more mature, and bring deeper thinking, we can ensure that the AI we develop evolves to become a better partner for us. An AI that reflects the best of us, not the worst. That means that everyone, especially the leadership teams of the leaner, smaller multinational companies and SMEs of the future will need to become deliberately developmental to get much better at collaboration and communication. So with the army of solopreneurs who exit companies to deliver part of the AI stack. In businesses of the future, as multiple external blockchains deliver new capabilities to the market, we will need a number of brilliant internal âquarterbacksâ calling the commercial, marketing, digital, operational, legal, and people âplaysâ and âthrowingâ out projects or tasks to their AI or human partners and solopreneurs across the decentralised web3 ecosystem. And the teams left inside those learner businesses need to develop too.
Truffle is a framework that provides compiling, testing and systematic project management for developing Ethereum decentralized applications. As of now, Truffle provides a way to easily deal with bundling node.js modules of decentralized application using the webpack tool. However, due to the Truffle project structure, server-side node.js modules such as network communication modules are not usable in a direct way. In this paper, to address this issue, we propose a method to use server-side node.js modules through Ethereum smart contracts and event processing mechanism. In the proposed method, a separate node application is associated to the server-side module to execute the module in response to the request of the decentralized application. To this end, we introduce the notion of function gateway, a smart contract for connecting two applications with Ethereum's event-watch processing technique. Also, to use the function gateway contract in a robust way, we introduce a robust function gateway that includes the process of confirming whether or not the event-watch has occurred and the node.js module function has been executed. In addition, we present a decentralized application using node.js module for sending actual e-mails based on the function gateway.
Lingfeng Guo, Yichen Guo, Tianzuo Zhang, Z. Hong Zhou
This paper explores the integrated application of robotics, blockchain, and software engineering in intelligent warehousing, achieving efficient collaboration and credible management. For software engineering and robotics integration, Model-Driven Architecture (MDA) combined with ROS 2 abstracts warehouse robots' environmental perception and motion control modules into independent models, boosting code reuse by over 40% and keeping system response delay within 50ms. To solve robots' poor path optimization and slow algorithm convergence under multiple constraints, an improved genetic algorithm-based path planning method is proposed. It uses grid method for environment construction, improves traditional genetic algorithm with deletion and smoothing operators plus niche method, and comparative experiments show it outperforms others in path length, smoothness, difficulty, and running time. In blockchain-robotics integration, Hyperledger Fabric-based alliance chain is applied to multi-robot task allocation, defining scheduling priority via smart contracts and relying on PBFT. Tests with 100 nodes show task conflict rate below 0.3 % and financial-grade data security (passing NIST SP 800â210). Software engineering's cross-layer framework addresses integration pain points: bottom-layer lightweight Wasm triples contract efficiency; application-layer Coq verifies protocol non-repudiation. This supports blockchain-driven dynamic allocation with 200 transactions/second throughput and stable end-to-end delay within 200ms, greatly enhancing warehousing efficiency.
The effectiveness of distributed ledger technology (DLTs), in particular blockchain, in improving the security and administration of massive distributed systems made up of independent agents is examined in this research. It looks at how these technologies are making the leap from lab settings to practical robotics uses. Recently, solutions that are resilient to sporadic connectivity and provide scalable frameworks for managed or permissioned networks have been presented, despite persistent concerns over scalability and practical implementation. While highlighting the numerous applications in which DLTs facilitate multi-robot systems, the paper also points out that the majority of research on open, permissionless blockchains is only applicable to a small number of robotics applications. As an alternative, the emphasis is now on permissioned blockchains and creative DLT architectures, which are propelling adoption in more conventional and industrial sectors.
C.M. Nalayini, A.R. Sathyabama, S. Priyadharshini, Sumathi. S
In the modern agricultural landscape, collaborative robots have emerged as key technology for enhancing precision, efficiency and sustainability in farming practices. This research introduces a Smart Cobot Greenhouse Assistant developed to automate plant health monitoring and management with controlled environment. It identifies plant's condition and take suitable actions like watering dry plants, raising alerts for diseased ones, and leaving healthy plants unharmed. A two-dimensional workspace is modelled where the cobot is initialized at the origin$(\mathbf{0, 0})$and plants are located at respective positions$(\mathbf{x, y})$. Dynamic states such as healthy, dry and diseased are assigned and simulated through python code using a well-defined synthetic dataset. Cobot's movements and actions are animated using Matplotlib visualization to produce an efficient and sustainable greenhouse management and the information are recorded into the blockchain distributed ledger and alerts are sent to the owner for further decision. Compared with the traditional system, the proposed smart cobot achieved operational responsiveness, dynamic visual feedback, and trustworthy data handling with full transparency.
Mehmed OÄuz Ĺen, FatÄąh OkumuĹ, Adnan FatÄąh Kocamaz
Decentralized task allocation is a critical challenge in multi-robot systems, particularly in scenarios where autonomy, scalability, and robustness are essential. While centralized approaches simplify coordination, they suffer from limitations such as single points of failure and poor scalability in dynamic environments. This paper presents a comparative evaluation of three decentralized and distributed task allocation algorithms integrated into a blockchain-powered multi-robot system where Hyperledger Fabric is used as blockchain platform. Each algorithm employs a cost-based selection mechanism to assign tasks autonomously while leveraging a distributed ledger for data consistency and conflict resolution. The algorithms -Euclidean distance, TEB motion planner and every robot computing all robots' costs- are evaluated for a system of three TIAGo++ robots in two different simulation environments. Performance metrics include computational overhead and task request conflict rates. Results show that while Euclidean distance offers the lowest overhead, it suffers from high conflict rates; TEB motion planner improves fairness with moderate overhead; and every robot computing all robots' costs ensures the highest consistency at the cost of increased computation. The findings highlight key trade-offs in decentralized coordination and offer guidance for designing scalable and reliable blockchain-powered multi robot systems.
By Elizabeth Enkin, University of Nebraska-Lincoln DOI: https://www.doi.org/10.69732/CKTL9913 As language teachers, we are keenly aware of the important benefits that Web 2.0, the collaborative web, has brought to language teaching. From social media to audio and visual tools, Web 2.0
The Agentic Service Ecosystem consists of heterogeneous autonomous agents (e.g., intelligent machines, humans, and human-machine hybrid systems) that interact through resource exchange and service co-creation. These agents, with distinct behaviors and motivations, exhibit autonomous perception, reasoning, and action capabilities, which increase system complexity and make traditional linear analysis methods inadequate. Swarm intelligence, characterized by decentralization, self-organization, emergence, and dynamic adaptability, offers a novel theoretical lens and methodology for understanding and optimizing such ecosystems. However, current research, owing to fragmented perspectives and cross-ecosystem differences, fails to comprehensively capture the complexity of swarm-intelligence emergence in agentic contexts. The lack of a unified methodology further limits the depth and systematic treatment of the research. This paper proposes a framework for analyzing the emergence of swarm intelligence in Agentic Service Ecosystems, with three steps: measurement, analysis, and optimization, to reveal the cyclical mechanisms and quantitative criteria that foster emergence. By reviewing existing technologies, the paper analyzes their strengths and limitations, identifies unresolved challenges, and shows how this framework provides both theoretical support and actionable methods for real-world applications.
Juan de Anda-SuĂĄrez, JosĂŠ Luis LĂłpez-RamĂrez, Daniel JimĂŠnez-Mendoza, JosĂŠ Manuel Benitez-Quintero ¡ 7 authors
Autonomous Vehicles (AV) have been extensively studied in both scientific and social contexts. Over the past two decades, there has been a significant rise in their real-world applications, including neural networks, Blockchain, Internet of Things, autonomous navigation, computer vision, automation processes, and various other areas. Hence, it is imperative to investigate the interplay between software, hardware, and individuals. To guarantee secure and unaffected interactions within autonomous vehicle devices and networks, decentralized Blockchain technology is proposed. This study presents the introduction of a framework we named âDEMU-NAVâ for an ecosystem that includes Artificial Intelligence (AI), humans, and robots. The framework makes use of a decentralized Blockchain, Smart-Contract (SC), and Internet of things (IoT) network. Our framework was implemented using Ethereum and Python, enabling us to oversee Blockchain, Smart-Contracts, and the IoT for the facilitation of autonomous vehicle navigation.
Mr. R. Suresh M. E, Mr. Mohamed Shalik. S, Mr. Joshva Jagan. A, Mr. Vigneshwaran. V
This venture presents a secure and private Web3 communication framework utilizing the Dual Reversible Secret Image Sharing Mechanism (DR-SISM). By utilizing wallet addresses for confirmation, it streamlines the method whereas guaranteeing security. DR-SISM safely encodes images into numerous offers, available as it were by the expecting beneficiary. The framework moreover coordinating AI-driven command help, permitting clients to send messages and share images utilizing normal dialect commands, making the stage user-friendly. This paper looks at existing communication advances and illustrates how combining DR-SISM, wallet-based informing, and AI makes a secure, adaptable Web3 arrangement.
In our pursuit of sustainable innovation for Intangible Cultural Heritage (ICH), we have adopted a methodology driven by the co-creation of human and artificial intelligence (AI). Our inclusive community, consisting of diverse stakeholders such as folk inheritors, professional choreographers, cultural center staff, square dance enthusiasts, designers, and AI engineers, forms a robust foundation for innovative practices. The communityâs outputs, including dataset, experimental dance, creative short film, digital 3D works, Non-Fungible Tokens (NFTs), and an App, are multi-modal transformable. We underscore the communal utilization of resources across diverse practices and advocate for the transformation of outputs across various modalities. Importantly, each of these practices integrates AI technology into the workflow, positioning it as a pivotal enabler for fostering sustainable innovation within the domain of ICH.
AI in Service Interactions
Artificial Intelligence in Healthcare and Education
Low-Rank Adaptation (LoRA) is a widely adopted method for customizing large-scale language models. In distributed, untrusted training environments, an open source base model user may want to use LoRA weights created by an external contributor, leading to two requirements: (1) the base model user must confirm that the LoRA weights are effective when paired with the intended base model, and (2) the LoRA contributor must keep their proprietary weights private until compensation is assured. We present ZKLoRA, a zero-knowledge verification protocol that relies on succinct proofs and our novel Multi-Party Inference procedure to verify LoRA-base model compatibility without exposing LoRA weights. ZKLoRA produces deterministic correctness guarantees and validates each LoRA module in only 1-2 seconds on state-of-the-art large language models. This low-latency approach enables nearly real-time verification and promotes secure collaboration among geographically decentralized teams and contract-based training pipelines. The protocol ensures that the delivered LoRA module works as claimed, safeguarding the contributor's intellectual property while providing the base model user with verification of compatibility and lineage.
Open access
2 source records
Geophysical Methods and Applications
Robotics and Automated Systems
Target Tracking and Data Fusion in Sensor Networks
Tatami puzzles are pencil puzzles with an objective to partition a rectangular grid into rectangular regions such that no four regions share a corner point, as well as satisfying other constraints. In this paper, we develop a physical card-based protocol called Tatami printer that can help verify solutions of Tatami puzzles. We then use the Tatami printer to construct zero-knowledge proof protocols for two such puzzles: Tatamibari and Square Jam. These protocols enable a prover to show a verifier the existence of the puzzles' solutions without revealing them.
The IOTA Extended UTXO (IOTA EUTXO) model extends the UTXO blockchain to include features like smart contracts and non-fungible tokens. In this work, we show that the IOTA EUTXO model maintains the base correctness properties of the UTXO model while extending it with extra functionality. We achieve this by specifying and verifying the essential concepts of the base UTXO model and the extensions proposed by IOTA using the Isabelle proof assistant. The specification is designed to be modular and extensible, meaning it can be used as a foundation for further research of the UTXO and IOTA EUTXO models.
An all-encompassing and flexible framework that links theoretical principles and actual execution is required for the creation of hardware for Web3.0 and edge intelligence. Decentralized identification, semantic data, blockchain, and zero-knowledge proofs are just few of the concepts that are examined in depth to provide the groundwork for this technique. The main goal is to figure out what kinds of hardware are needed to implement these theoretical principles. Subsequently, the technique continues to extract the hardware requirements, distinguishing the unique demands, problems, and performance criteria important for enabling Web3.0 and edge intelligence. These needs include a wide range of topics, including performance, safety, efficiency, scalability, and even compatibility. Once the theoretical principles and hardware requirements are fully understood, the technique moves on to the design step. Key to realizing these abstract ideas is the development of specialized hardware architectures and components. Based on the outcomes of the performance assessment, iterative refinement is carried out to fix the hardware's flaws and enhance its functionality. As a result of this iterative process, hardware is kept up to date to suit the ever-shifting requirements of Web3.0 and edge intelligence. The suggested technique concludes with an emphasis on flexibility and future-proofing in light of the everchanging nature of Web3.0 and edge intelligence. Keeping up with technology developments and reevaluating the hardware design as needed are both part of this process.