Khoya (khoa or mawa) is a traditional dairy product, prepared by heating and concentrating milk, which is widely used in preparation of indigenous milk sweets. But, challenges such as process variability, quality deterioration, microbial contamination, adulteration, limited shelf life and inefficient supply chain management hinder its production and distribution. New solutions to these challenges are available across the khoya value chain due to recent advancements in artificial intelligence (AI) and Industry 4.0 technologies. This review highlights the applications of AI in khoya processing, packaging, transportation, distribution and quality management. The role of machine learning, deep learning, computer vision, Internet of Things (IoT), digital twins, smart sensors, and blockchain in process optimization, automated quality inspection, adulteration detection, shelf-life prediction, intelligent packaging, cold-chain monitoring, logistics optimization and demand forecasting is explored. We also review AI-enabled analytical tools for rapid and non-destructive quality assessment, such as hyperspectral imaging, electronic nose, and electronic tongue. The review also discusses the contribution of AI to improving food safety, traceability, sustainability and operational efficiency, as well as to reducing post-harvest losses and environmental impacts. Finally, the paper discusses the existing challenges, future research directions, and prospects of AI-enabled smart dairy manufacturing. The review finds that AI can play a significant role in improving the quality, safety, efficiency, and sustainability of the khoya industry and helping its transition to intelligent and data-driven dairy processing.
Meeting the global demand for fresh, minimally processed food requires us to rethink how we monitor food safety. Traditional laboratory methods are often too slow, labor-intensive, and impractical for real-time applications. To overcome these delays, biosensors have emerged as a rapid, highly sensitive, and cost-effective alternative. This study explores how biosensing technology accurately detects pathogens, chemical contaminants like heavy metals and pesticides, and spoilage indicators across dairy, meat, produce, and packaged foods. What makes these tools truly transformative is their seamless integration with modern digital infrastructure. By combining biosensors with the Internet of Things (IoT), artificial intelligence (AI), nanotechnology, edge computing, and blockchain, we can create intelligent, continuous monitoring systems. These interconnected frameworks allow for real-time, farm-to-fork traceability, enabling early hazard detection, extending shelf life, and significantly reducing food waste through data-driven decisions. Despite this immense potential, bringing smart biosensors to the commercial market involves overcoming distinct practical hurdles. We examine current technical barriers, including biofouling, long-term sensor stability, power management, and high manufacturing costs. More importantly, we highlight the emerging innovations actively solving these bottlenecks, such as biodegradable materials, battery-free platforms, advanced printed electronics, and smart packaging technologies.
The technical architecture establishes a multi-node data certification platform via consortium blockchain, integrates the InterPlanetary File System (IPFS) for distributed encrypted storage of experimental data, and automates ethical reviews, experimental protocol supervision, and resource allocation through smart contracts. Innovatively, the system mints NFT-based digital identity certificates with unique digital fingerprints to comprehensively document genetic profiles, experimental histories, and medical records of individual mice, ensuring verifiability and tamper-resistance of full-lifecycle data.At the governance level, a token-based economic model and decentralized autonomous organization (DAO) framework are introduced. Dynamic incentive mechanisms promote secure cross-institutional research data sharing, while on-chain voting protocols enable decentralized scientific decision-making, effectively balancing open data access with privacy protection requirements. This system establishes a trusted data infrastructure spanning "biological individuals-experimental processes-research outcomes," providing a scalable Web 3.0 paradigm for digital transformation in life sciences. It drives the evolution of laboratory animal management toward intelligent, standardized, and ethics-compliant practices.
Chunghwan Jung, Soo-Jung Kim, Jaehyuck Jang, Joo Hwan Ko · 9 authors
The development of real-time and sensitive humidity sensors is in great demand from smart home automation and modern public health. We hereby proposed an ultrafast and full-color colorimetric humidity sensor that consists of chitosan hydrogel sandwiched by a disordered metal nanoparticle layer and reflecting substrate. This hydrogel-based resonator changes its resonant frequency to external humidity conditions because the chitosan hydrogels are swollen under wet state and contracted under dry state. The response time of the sensor is ~10 4 faster than that of the conventional Fabry-Pérot design. The origins of fast gas permeation are membrane pores created by gaps between the metal nanoparticles. Such instantaneous and tunable response of a new hydrogel resonator is then exploited for colorimetric sensors, anti-counterfeiting applications, and high-resolution displays.
Ronan D. Mendonça, Otávio Santos Gomes, Luiz F. M. Vieira, Alex Borges Vieira · 6 authors
In this paper, we propose a blockchain-based cold chain technology for vaccine cooling track. The COVID-19 pandemic has caused the death of millions of people. An important step towards ending the pandemic is vaccination. Vaccines must be kept under control temperature during the whole process, from fabrication to the hands of the health professionals who will immunize the population. However, there are numerous reports of vaccine loss due to temperature variations, and, currently, people getting vaccinated have no control if their vaccine was kept safe. Blockchain is a technology solution that can provide public and verifiable records. We review the World Health Organization (WHO) cool chain and Blockchain technology. Moreover, we describe current IoT temperature monitoring devices and propose Blockcoldchain to track vaccine cold chain using blockchain, thus proving an unalterable vaccine temperature history. Our experimental results using smart contracts demonstrate the system's feasibility.
Dixon Vimalajeewa, Subhasis Thakur, John G. Breslin, D.P. Berry · 5 authors
The use of Internet of Things (IoT) with the Internet of Nano Things (IoNT) can further expand decision making systems (DMS) to improve reliability as it provides a new spectrum of more granular level data to make decisions. However, growing concerns such as data security, transparency and processing capability challenge their use in real-world applications. DMS integrated with Block Chain (BC) technology can contribute immensely to overcome such challenges. The use of IoNT and IoT along with BC for making DMS has not yet been investigated. This study proposes a BC-powered IoNT (BC-IoNT) system for sensing chemicals level in the context of farm management. This is a critical application for smart farming, which aims to improve sustainable farm practices through controlled delivery of chemicals. BC-IoNT system includes a novel machine learning model formed by using the Langmuir molecular binding model and the Bayesian theory, and is used as a smart contract for sensing the level of the chemicals. A credit model is used to quantify the traceability and credibility of farms to determine if they are compliant with the chemical standards. The accuracy of detecting the chemicals of the distributed BC-IoNT approach was >90% and the centralized approach was <80%. Also, the efficiency of sensing the level of chemicals depends on the sampling frequency and variability in chemical level among farms.
IoT-enable monitoring can provide valuable information for the shellfish quality evaluation during cold storage condition. However, IoT based information storage relies on the centralized platform, it is possible to tamper. In this paper, we establish blockchain based multi-sensors (WSN) monitoring system to collect quality parameters and verify captured information for improving transparency and trust during cold storage. The implementation of the K-means and SVM algorithms were used in quality evaluation applications to classify and predict the quality loss of frozen shellfish. The results show blockchain based WSN monitoring can achieve the dynamic indicators continuous monitoring and ensures the data security and reliability. The proportion of the training set and the test set in the allowable deviation range is 88.89% and 87.17%. The root mean square error (RMSE) of training set and test set are 0.1502 and 0.1793 by SVM model. The performance of the K-means and SVM model has higher accuracy than BP model. This paper could help to reduce the risk of food losses and improve quality and safety management of frozen shellfish during cold storage.
Shengjing Sun, Xiaochen Zheng, Javier Villalba-Díez, Joaquín Ordieres‐Meré
Indoor air pollution has been ranked among the top five environmental risks to public health. Indoor Air Quality (IAQ) is proven to have significant impacts on people's comfort, health, and performance. Through a systematic literature review in the area of IAQ, two gaps have been identified by this study: short-term monitoring bias and IAQ data-monitoring solution challenges. The study addresses those gaps by proposing an Internet of Things (IoT) and Distributed Ledger Technologies (DLT)-based IAQ data-monitoring system. The developed data-monitoring solution allows for the possibility of low-cost, long-term, real-time, and summarized IAQ information benefiting all stakeholders contributing to define a rich context for Industry 4.0. The solution helps the penetration of Industrial Internet of Things (IIoT)-based monitoring strategies in the specific case of Occupational Safety Health (OSH). The study discussed the corresponding benefits OSH regulation, IAQ managerial, and transparency perspectives based on two case studies conducted in Spain.