Forecasting of the time series data is a challenge as its details are more complex in nature. Climate change is a global issue as it influences the environment and it impacts directly affecting the human and the marine species. Global warming is a big threat and it reflects in sea temperature. Due to the rising sea temperature, the fishes like sardine and pelagic are not getting the living sea environment and the annual catchment of these fishes are reduced. The fishes are drifted from one place to other. This paper focuses on forecasting these fishes based on the catchment of historical data. The proposed approach incorporates the Multivariate Imputation by Chained Equations (MICE) is used to determine the missing values. The Auto Regressive Integrated Moving Average (ARIMA) model is blended for predicting the upfront values. The proposed approach is tested with various parameters and the test results shows its efficiency.

Indiscriminate use of chemical agents like calcium carbide and ethephon for the ripening of fruits poses grave health hazards, emitting carcinogenic and neurotoxic compounds. Here we present a new, scalable, inexpensive, internet of things (IoT)-enabled electronic nose (e-nose) AI-Bot system for the detection of chemically ripened fruits. This would involve the development of a system that uses an MQ-3 gas sensor to quantify the ethanol content, as well as an MQ-135 gas sensor with an ESP32 microcontroller to quantify even further the amount of volatile organic compounds (VOCs) suggestive of artificial ripening. Flutter-based mobile application allows real-time monitoring, ripening classification using machine learning (ML) algorithms, and logging the historical data. A small sample was taken for inter-document feature literature mining, modelling sensor behaviors according to voltage dividers and gas concentration resistance laws for robust calibration and classification performance. Validation studies were performed on mango, banana, and papaya fruit in the laboratory environment. Total 75 samples (25 each of banana, mango, papaya across 3 trials) of fruit were tested. The implemented system achieved 95% for banana, 92% for mango, and 90% classification accuracy for papaya when cross validated.

Ensuring data security and privacy has emerged as a serious concern in the realm of blood supply chain. This is mainly because of sensitivity of donor information, the involvement of multiple stakeholders, and the need for transparent traceability. This paper proposes a novel privacy-preserving, permissioned blockchain framework for blood supply chain management that integrates Hyperledger Fabric, the InterPlanetary File System (IPFS), and a Zero-Knowledge Proof (ZKP)-based authentication protocol. The framework introduces a Pseudonymous Role-Bound Zero-Knowledge Authentication (PRZKA) mechanism that enables donors to authenticate and authorize access to their medical data without revealing their real identities. Context-specific pseudonyms derived through cryptographic hash-to-curve operations ensure unlinkability across different healthcare interactions, while Schnorr-style challenge–response proofs prevent replay attacks and credential misuse. Sensitive donor information is protected using Fabric Private Data Collections, whereas encrypted medical records are stored off-chain in IPFS, with only secure content identifiers recorded on the blockchain. Smart contracts enforce fine-grained, consent-aware access control policies and maintain immutable audit logs of all access events. The proposed system architecture combines an off-chain ZKP gateway with on-chain authorization logic to minimize blockchain overhead while preserving strong security guarantees. Furthermore, a performance evaluation framework is defined, including metrics, workload scenarios, and system configurations, to support future empirical validation. Security analysis indicates that the proposed framework enhances privacy, prevents identity linkage, and enables auditable, consent-driven data sharing compared with existing blockchain-based healthcare solutions.