Blockchain Papers

Swati Sumit Vaidya, Charanjeet Singh, Omar Isam Al Mrayat, Ansal Valappil · 6 authors

No abstract is available for this record.

Chigozie Athanasius Nnadiekwe, Collins Izuchukwu Okafor, Ikechi Saviour Igboanusi, Jae Min Lee · 5 authors

SoldierCare is a real-time, blockchain-enabled Internet of Medical Things (IoMT) framework designed to enhance military personnel safety through integrated health monitoring and cyberattack detection. The system employs a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model trained on the WUSTL-EHMS-2020 dataset, combining physiological sensor data and network traffic to identify both health anomalies and malicious activities with high accuracy. A smart contract-enabled Ethereum blockchain ensures the integrity and traceability of alerts by immutably logging metadata, while detailed data is stored off-chain in IPFS to reduce on-chain overhead. The architecture supports edge deployment, enabling low-latency inference and autonomous operation in mission-critical environments. Experimental results demonstrate a detection accuracy of 98.6%, with efficient scaling and minimal false detections. Optimizations such as transaction batching enhance blockchain performance under increasing load. SoldierCare represents a secure, scalable solution that fuses AI, fog computing, and blockchain to provide resilient operational support in dynamic battlefield scenarios.

Chong Yang, Keli Chen, Zhuhua Hu, Yaochi Zhao · 6 authors

With the rapid development of communication technology, the efficient utilization and management of spectrum resources have become a critical issue for the performance and reliability of wireless communication networks. Collaborative spectrum sensing, as an important technology for enhancing spectrum utilization, can significantly improve the accuracy of spectrum sensing through multi-node cooperation. However, existing methods face challenges such as malicious node behavior, data tampering, and unfair resource allocation in practical applications, thereby severely constraining the performance and security of spectrum sensing systems. In response to these issues, this paper proposes a blockchain-based collaborative spectrum sensing system and introduces two key innovations focusing on spectrum sensing and resource optimization: Firstly, an innovative hybrid consensus mechanism called Proof of Authority and Stake (PoAS) has been designed. It organically combines the efficiency of authoritative nodes with the fairness of stake distribution, thus optimizing the consensus process of the blockchain and ensuring the timeliness and trustworthiness of spectrum sensing data. Secondly, a detection method for malicious users is proposed based on game theory, which identifies and suppresses the behavior of malicious nodes in real-time through a dynamic reputation mechanism, thereby enhancing both the accuracy of spectrum sensing and the robustness of the system. Additionally, this paper constructs a collaborative sensing framework that integrates optimized spectrum resource allocation, striking a balance between sensing performance and resource allocation efficiency. Experimental results indicate that the system proposed in this paper, when compared to the single PoAS hybrid mechanism, can elevate the detection probability from 0.5 to 0.9 through the implementation of the PoAS+ game theory mechanism. Furthermore, the average difference in node revenue is enhanced by 454 units, thereby augmenting the accuracy of spectrum sensing and improving resource utilization.

Ali Shakerian, Ali Eghmazi, Justin Goasdoué, René Landry

This paper proposes a novel Blockchain-based indoor navigation system that combines a foot-mounted dual-inertial measurement unit (IMU) setup and a zero-velocity update (ZUPT) algorithm for secure and accurate indoor navigation in GNSS-denied environments. The system estimates the user's position and orientation by fusing the data from two IMUs using an extended Kalman filter (EKF). The ZUPT algorithm is employed to detect and correct the error introduced by sensor drift during zero-velocity intervals, thus enhancing the accuracy of the position estimate. The proposed Low SWaP-C blockchain-based decentralized architecture ensures the security and trustworthiness of the system by providing an immutable and distributed ledger to store and verify the sensor data and navigation solutions. The proposed system is suitable for various indoor navigation applications, including autonomous vehicles, robots, and human tracking. The experimental results provide clear and compelling evidence of the effectiveness of the proposed system in ensuring the integrity, privacy, and security of navigation data through the utilization of blockchain technology. The system exhibits an impressive ability to process more than 680 transactions per second within the Hyperledger-Fabric framework. Furthermore, it demonstrates exceptional accuracy and robustness, with a mean RMSE error of 1.2 m and a peak RMSE of 3.2 during a 20 min test. By eliminating the reliance on external signals or infrastructure, the system offers an innovative, practical, and secure solution for indoor navigation in environments where GNSS signals are unavailable.

Bilash Saha, Md. Saiful Islam, Abm Kamrul Riad, Sharaban Tahora · 6 authors

Falls among the elderly are a major health concern, frequently resulting in serious injuries and a reduced quality of life. In this paper, we propose "BlockTheFall," a wearable device-based fall detection framework which detects falls in real time by using sensor data from wearable devices. To accurately identify patterns and detect falls, the collected sensor data is analyzed using machine learning algorithms. To ensure data integrity and security, the framework stores and verifies fall event data using blockchain technology. The proposed framework aims to provide an efficient and dependable solution for fall detection with improved emergency response, and elderly individuals' overall well-being. Further experiments and evaluations are being carried out to validate the effectiveness and feasibility of the proposed framework, which has shown promising results in distinguishing genuine falls from simulated falls. By providing timely and accurate fall detection and response, this framework has the potential to substantially boost the quality of elderly care.

Sivajothi Paramasivam, Chua Huang Shen, Alireza Zourmand, Amira Kamil Ibrahim · 6 authors

The increasing spread of the coronavirus across countries and with no sight of vaccine uncovered soon has prompted affected countries to impose strict containment measures. In view to ease the enormous strain on health systems; disinfection, decontamination, contact tracking, and isolation are a few health protocols that are to be observed by companies that resumed their activities to protect their employees from being infected. Hence, against a backdrop of heightened uncertainty, this project leverages on the advancement of technology to design and built a smart Infrared thermal scanning with a camera (Thermovis-Mi-FRAHT-800). An Ultraviolet-C spectrum disinfection system and integration of blockchain technology for data sharing, managing health records, and access control. SketchUp used as a 3D design platform for this project. This system designed with a precautionary measure which includes 3 conditions to be met for the automated barrier to be open which include temperature measurement, disinfection, and sanitization processes. Overall, a person spends less than a minute in the walkthrough path chamber as the process takes 20 to 25 seconds each. By this calculation, we assume that 2 people would be able to get disinfected within a minute which comes up to 120 people per hour. Thus, reducing the number of monitoring staffs in direct contact with the stakeholders with potential infection issues. It is envisaged that developing this conceptual design would be the cornerstone in adhering to control measure through appropriate infection control and modification using current and future technologies.

Tiago M. Fernández‐Caramés, Iván Froiz-Míguez, Óscar Blanco-Novoa, Paula Fraga‐Lamas

Diabetes patients suffer from abnormal blood glucose levels, which can cause diverse health disorders that affect their kidneys, heart and vision. Due to these conditions, diabetes patients have traditionally checked blood glucose levels through Self-Monitoring of Blood Glucose (SMBG) techniques, like pricking their fingers multiple times per day. Such techniques involve a number of drawbacks that can be solved by using a device called Continuous Glucose Monitor (CGM), which can measure blood glucose levels continuously throughout the day without having to prick the patient when carrying out every measurement. This article details the design and implementation of a system that enhances commercial CGMs by adding Internet of Things (IoT) capabilities to them that allow for monitoring patients remotely and, thus, warning them about potentially dangerous situations. The proposed system makes use of smartphones to collect blood glucose values from CGMs and then sends them either to a remote cloud or to distributed fog computing nodes. Moreover, in order to exchange reliable, trustworthy and cybersecure data with medical scientists, doctors and caretakers, the system includes the deployment of a decentralized storage system that receives, processes and stores the collected data. Furthermore, in order to motivate users to add new data to the system, an incentive system based on a digital cryptocurrency named GlucoCoin was devised. Such a system makes use of a blockchain that is able to execute smart contracts in order to automate CGM sensor purchases or to reward the users that contribute to the system by providing their own data. Thanks to all the previously mentioned technologies, the proposed system enables patient data crowdsourcing and the development of novel mobile health (mHealth) applications for diagnosing, monitoring, studying and taking public health actions that can help to advance in the control of the disease and raise global awareness on the increasing prevalence of diabetes.

Jitesh Pabla, Vaibhav Sharma, Rajalakshmi Krishnamurthi

Currently, a state's army is considered a vital tool for its security. Therefore, tracking and monitoring the health and position of a soldier becomes necessary to ensure their safety. In recent years, a lot of technological advances happen in the field of sensors. One of the popular areas utilizing sensors is developing human healthcare system to monitor vital body signals. The network of such sensors that are used to monitor vital human signal for health care is called Body Sensor Network (BSN). Similarly, a small GPS module can be used to track a person's location. In this paper, we describe a system comprising of a sensor module to be mounted on a soldier's arm for real-time health and position monitoring, which transmits and stores a soldier's data in an encrypted form in a BlockChain; thus making the data tamper proof and distributed. The mounted sensor module consists of a temperature, heart-rate, and GPS module, with 1.15%, 11.1% relative errors in the sensors respectively and 1.62 m, 2.05 m deviation in latitude and longitude of the GPS module in their readings compared against commercial devices. The BlockChain will exist on army controlled computers.

Tayyaba Tariq, Rana Muhammad Amir Latif, Muhammad Farhan, Adil Abbas · 5 authors

Patient wears a heartbeat sensor bracelet and set the settings accordingly. Doctors get notification via the different use of technology if a patient's heartbeat is out of range to given specific limits to monitor heart rate is very important for heart patients because it shows the condition of the there is any disease that will be identifiable. Although Electrocardiography (ECG) is used to check heartbeat, the (ECG) Electrocardiography machine shows a rare form. A method to check heartbeat could be heartbeat sensor which is in different sizes and shapes that are a more natural way to measure heartbeat, and most of them are available in smart straps, smartphone and so on. Indicates the heart is expanding and contracting. The opinion on this is to use the specific bracelet category machine to check the heartbeat and then upload data on the website to maintain the patient's history. A Website is available for those patients who are registered with a doctor-patient history updates side by side. The system provides more reliability, efficiency, and accuracy to monitor the heartbeat. Patient History will be available to the doctor as well. However, the doctor will recommend medication for it. By using the Machine learning tools and techniques for the analysis of data and regression technique for regular approach usage. Circos tool is being used for the design view of the dataset result. Linear Regression (LM) algorithm and Classification and Regression Tree algorithm (CART) used in R-language for the results analyzing the heartbeat and the detection of heart rate. IoT is ultimately the amalgamation of both software and hardware to make trillions of information by linking multiple tactics and sensors with the cloud and making sense of data and information with creative tools.