Traditional rating scale surveys often encounter challenges such as data integrity issues due to lack of transparency leading to an un-auditable situation. These challenges can be overcomed by harnessing the capabilities of XNO's 1 block-lattice data structure and public distributed ledger technology while enhancing the efficiency, security, reliability of rating scale surveys ensuring immutability and transparency of data. Participants can be incentivized for responding to surveys through XNO micropayments, eliminating any intermediaries. The underlying technology of XNO ensures survey data integrity, prevents manipulation along with providing an auditable and tamper-proof record of survey results. This work also discusses a strategy for analyzing survey data collected through XNO transactions.

The proliferation of Internet of Things (IoT) devices in various domains necessitates efficient and scalable deployment strategies. Over-the-Air (OTA) programming has traditionally been employed for updating IoT devices, but its limitations become apparent in large-scale deployments due to time needed for updation of huge number of IoT devices, bandwidth constraints and latency issues. To address these challenges, this research introduces a novel Cloud-Processed IoT Framework leveraging On-the-Fly (OTF) programming technique. The framework optimizes deployment scalability by offloading processing tasks to the cloud, minimizing device-side computation and eliminating OTA data transmission. OTF programming enables instant updation and execution, allowing IoT devices to adapt and respond to changing requirements without the need for manual firmware updates. This paper presents the architecture of the proposed framework, highlighting its key components and functionalities. Through this innovative approach, the Cloud-Processed IoT Framework offers a promising solution for managing and updating IoT deployments in resource-constrained environments, paving the way for enhanced scalability and agility in IoT ecosystems.

The proliferation of Internet of Things (IoT) devices has led to an increasing need for secure and efficient methods of remote control. Traditional approaches often face challenges related to security vulnerabilities and centralized control mechanisms. This paper proposes a novel methodology for remotely controlling IoT devices utilizing micropayments of XNO, a blockchain-based cryptocurrency. The methodology leverages the decentralized nature of blockchain technology to ensure secure and transparent transactions, while micropayments facilitate cost-effectiveness. Through simulation, we demonstrate the effectiveness and feasibility of our proposed methodology in real-world IoT environments. Overall, our approach offers a solution for remote IoT device control, addressing key challenges while paving the way for a more secure and decentralized IoT ecosystem.

Tracking and tracing of assets using decentralized systems demand optimized data formats to balance storage costs and retrieval performance. This paper proposes a cost-ef ective sensor data format tailored for decentralized storage of geographic point locations on XNO, a distributed ledger technology. The proposed format optimizes storage by encoding location data in a compact yet retrievable manner, leveraging spatial indexing techniques to facilitate ef icient and transparent querying. This solution presents a promising approach for scalable and af ordable asset tracking and tracing using the highly available and transparent decentralized environments, with potential applications across various industries.