Parvataneni Rajendra Kumar, S. Meenakshi, S. Shalini, S. Devi · 5 authors
The integration of deep learning and blockchain technologies has the potential to revolutionize soil quality prediction in smart agriculture. Deep learning models, like neural networks and convolutional neural networks, enable accurate predictions of soil properties by considering intricate relationships within data. Contextual learning approaches, including embeddings and data fusion, enrich the prediction process by incorporating external factors like weather conditions and land management practices. Blockchain technology ensures secure storage of predictions and data, while smart contracts facilitate automated model execution. This integrated system empowers farmers with accurate predictions for optimal resource allocation and fosters collaboration through decentralized data sharing. Future directions include advancements in deep learning algorithms, blockchain applications, and potential integration with IoT and remote sensing technologies.
Smart Agriculture and AI
Artificial Intelligence and Decision Support Systems
This research presents a solution that combines deep learning-based image processing, blockchain technology, and the Internet of Things (IoT) to achieve smarter control and traceability in greenhouse operations within the agricultural sector. By integrating these technologies, the aim is to overcome challenges posed by climate change, plant growth, limited agricultural land, and water scarcity, while enhancing crop yields and ensuring efficient and secure operations. The proposed system automates image capture, measurement, storage, and monitoring of environmental parameters in greenhouses, utilizing highly accurate image processing techniques with a 98% success rate. The integration of blockchain technology establishes an immutable and transparent record of transactions and data points, thereby improving traceability across the agricultural supply chain. This comprehensive approach fosters accountability, transparency, and trust, empowering consumers to make well-informed decisions regarding the products they purchase. Ultimately, this research contributes to advancing efficient and sustainable agricultural practices.
Smart farming, as a branch of the Internet of Things (IoT), combines the recognition of agricultural economic competencies and the progress of data and information collected from connected devices with statistical analysis to characterize the essentials of the assimilated information, allowing farmers to make intelligent conclusions that will maximize the harvest benefit. However, the integration of advanced technologies requires the adoption of high-tech security approaches. In this paper, we present a framework that promises to enhance the security and privacy of smart farms by leveraging the decentralized nature of blockchain technology. The framework stores and manages data acquired from IoT devices installed in smart farms using a distributed ledger architecture, which provides secure and tamper-proof data storage and ensures the integrity and validity of the data. The study uses the AWS cloud, ESP32, the smart farm security monitoring framework, and the Ethereum Rinkeby smart contract mechanism, which enables the automated execution of pre-defined rules and regulations. As a result of a proof-of-concept implementation, the system can detect and respond to security threats in real time, and the results illustrate its usefulness in improving the security of smart farms. The number of accepted blockchain transactions on smart farming requests fell from 189,000 to 109,450 after carrying out the first three tests while the next three testing phases showed a rise in the number of blockchain transactions accepted on smart farming requests from 176,000 to 290,786. We further observed that the lesser the time taken to induce the device alarm, the higher the number of blockchain transactions accepted on smart farming requests, which demonstrates the efficacy of blockchain-based poisoning attack mitigation in smart farming.
In traditional fruit traceability systems, the opacity of the process and the ease of data tampering have always been major challenges. To address this, we propose a fruit traceability system based on blockchain and computer vision in this paper. In terms of data storage, we chose the Ethereum blockchain to ensure the authenticity of the data. As the fruit passes through each node, we upload the fruit image and conduct quality checks. We trained the YOLOv5 model to identify fruit types, and on this basis, we trained an improved Unet model for saliency detection to extract the fruit image area, both of which performed very well. Based on the fruit image, we evaluate from four aspects: saturation, hue, defects, and shape. This system can be used for traceability throughout the fruit supply chain.
This work exploits the potential of two important technologies which are UAVs (Unmanned Aerial Vehicles) and blockchain in the context of Agriculture 4.0. We propose a cattle health monitoring system based on UAVs that collect health measures from IoT devices equipping the animals. The main objectives of our system are twofold. First, the consumer will be aware of the quality of his/her food. Second, the national ecosystem (e.g. agriculture ministry, trade ministry) will get useful information about the quality and the number of cattle that can be put on the market. Thus, smart cattle management strategies could be undertaken afterward. The involved entities in such a system are multiple: the farmer, the veterinaries, the ministry of agriculture, etc… We first start by studying the system’s security by applying the FMEA risk assessment methodology. Our findings motivate us to integrate blockchain technology to manage the data collected as well as the attribution of the UAVs missions via a marketplace. Thanks to its properties, this technology ensures the transparent tracking of cattle status and fairness in the payment of the UAVs managed by private operators. Finally, we develop a proof of concept using the Sui blockchain platform.
The metaverse is a virtual world, consisting of a collective virtual shared space where users can interact with one another through avatars and computer-generated objects. Its goal is to mimic our real world as closely as possible, integrating elements of various trends like AI, immersive reality, advanced connectivity, and Web3. While there is currently no universally accepted definition of the metaverse, the emergence of metaverse technologies across multiple sectors, including animal farming, is rapidly gaining momentum. The potential value of the metaverse, particularly in relation to its capacity for solving complex problems (e.g., climate change and sustainability) in precision food production systems makes it an exciting endeavor. However, it is crucial to consider ethical implications during the development of metaverse technologies for modern animal farming, given the sensitive and controversial nature of animal welfare. Failure to address these ethical considerations could lead to a lack of credibility and insensitivity towards the adoption of metaverse technologies in the animal farming sector. It is therefore important to ensure that the development of metaverse technologies does not prioritize technology over animal welfare, ethics, and socio-economic implications. Additionally, addressing the topic of diversity and equity in the context of animal farming and the metaverse is crucial to avoid perpetuating existing inequalities during the implementation of metaverse technologies. The purpose of this critical review is to stimulate dialogue among stakeholders such as farmers, animal scientists, bioengineers, veterinarians, policymakers, consumers, and business-to-business clients. It aims to help them better understand the potential and power of the metaverse, identify ethical implications and strategic imperatives, and act as a force for its positive evolution.
Smart farming is generally defined as an IT-based intelligent farming system that finds, analyses, and manages field variability by carrying out crop production activities at the right location, time, and method for maximum profitability, sustainability, and land resource conservation. Precision farming can result in high profitability and production but heavily depends on the accuracy of provided data and decision-making. While IoT can be very handy in collecting and processing crop and environment data in a precise and timely manner, at the same time, Blockchain technology can be utilized to preserve the sense data and provide a platform for the immutability of records to accurately and precisely store the crop products data and environment. Integrating Blockchain and IoT technologies in precision farming can manage the requirements of precision farming in developing an intelligent application that will minimize resource consumption and help in high crop yield while maintaining quality standards. Although there are several benefits of adopting smart agriculture and IoT-based technologies, there are several security concerns related to these technologies. This article reviews the basics of smart agriculture, components, and security issues. Further, it proposes a blockchain-based model for the secure integration of smart agriculture components to provide security and reliability.
Agriculture, encompassing industrialization, security, traceability, and sustainable resource management, is critical to the survival of humans. As resources dwindle, it is critical to develop strategies to assist in preserving agriculture. The development of the Internet of Things (IoT), Artificial intelligence, UAVs, and Blockchain technologies as new sectors has the potential to significantly improve the status of the Agricultural domain. In this context, this study does a comprehensive assessment of the literature to analyse the most recent breakthroughs in schemes that can innovate the agriculture domain. Following the determination of the fundamental needs in smart agriculture, several solutions and projects are highlighted. Furthermore, the present investigation will help in the identification of new avenues for future research related to the employment of AI, UAVs, and BC in agriculture.
This paper presents intuitive directions for field research by introducing a ground-breaking IoT-ML-driven intelligent farm management platform. This study’s main goal is to address agricultural difficulties by providing a thorough, integrated solution. This work makes a variety of important contributions. By utilizing cutting-edge technology like IoT and Machine Learning (ML), it first improves conventional farm management procedures. Farmers now have the capacity to remotely monitor and regulate irrigation management thanks to sensor-based real-time data. Second, based on data gathered from agricultural fields, our machine learning model offers improved water control management and fertilizer use recommendations, maximizing production while minimizing resource usage. The suggested solution also uses blockchain technology to create a safe, decentralized network that guarantees data integrity and defends against threats. We also introduce energy harvesting technology to address the issue of continuous energy supply for IoT devices, which lessens the load on farmers by removing the requirement for additional batteries. We achieved 89.5% accuracy in our proposed machine learning model. The suggested model would provide a variety of services to farmers, including pesticide recommendations and water motor control via mobile applications and a cloud database.
Julio César Úbeda Ortega, Jesús Rodríguez-Molina, Margarita Martínez, Juan Garbajosa
Livestock monitoring often requires human supervision to guide farm animals to a specific point and the displacement of workers to the places where these animals are, which is likely to be several kilometers away, thus resulting in a repetitive task that requires a significant amount of time and demands the usage of land vehicles capable of moving swiftly through the countryside. In addition to that, data collection about animal behaviour with such procedures is often insufficient and cannot be shared in a secure enough manner. This paper describes how Using Unmanned Aerial Vehicles (UAVs) tailored for this kind of task, when combined with other protocols and software technologies, can provide a useful to mitigate these issues. To prove this end, a functional prototype has been designed, built and tested, offering the operator accurate monitoring of farm facilities and animals. Additionally, security has been conceived as a cornerstone of the presented system from the very beginning. Not only the communication protocols used for this purpose have built-in security layers, but also InterPlanetary File System (IPFS) and blockchain have been used as the technologies that enhance data storage among peers in a network.
Ch G V N Prasad, A. Mallareddy, M. Pounambal, Vijayasherly Velayutham
The advancement of Internet-based technologies has made huge progress toward improving the accessibility of "smart agriculture." With the advent of unmanned and automatic management, smart agriculture is now able to accomplish monitoring, supervision, and real-time picture monitoring. It is not possible to know for sure that the data in a smart agriculture system is complete and secure from intrusion. This article investigates and assesses the potential of edge computing and blockchain for use in smart agriculture. We combine the advantages of blockchain technology and the edge computing framework to create a smart agriculture framework system that is based on a very straightforward analysis of the evolution of smart agriculture. The study proposes a thorough method for emphasizing the significance of agriculture and edge computing, as well as the advantages of incorporating blockchain technology in this context. This paper also proposes an intelligent agricultural product traceability system design: edge computing with blockchain for smart agriculture. The study concludes with a discussion of outstanding problems and difficulties that can arise during the creation of a blockchain-based edge computing system for smart agriculture systems.
Xiujuan Wang, Mengzhen Kang, Hequan Sun, Philippe De Reffye · 5 authors
Briefing: The demand for food is tremendously increasing with the growth of the world population, which necessitates the development of sustainable agriculture under the impact of various factors, such as climate change. To fulfill this challenge, we are developing Metaverses for agriculture, referred to as AgriVerse, under our Decentralized Complex Adaptive Systems in Agriculture (DeCASA) project, which is a digital world of smart villages created alongside the development of Decentralized Sciences (DeSci) and Decentralized Autonomous Organizations (DAO) for Cyber-Physical-Social Systems (CPSSs). Additionally, we provide the architectures, operating modes and major applications of DeCASA in Agri-Verse. For achieving sustainable agriculture, a foundation model based on ACP theory and federated intelligence is envisaged. Finally, we discuss the challenges and opportunities.
Md. Akkas Ali, B. Balamurugan, Rajesh Kumar Dhanaraj, Vandana Sharma
Food security seems to be a more prevalent concern for all countries throughout the world due to global population growth, dwindling natural resources, agricultural land, and an increase in unfavorable environmental circumstances. These problems are the driving force behind agriculture industry’s migration towards modern agriculture through the use of IoT and Blockchain technology for improving operations, productivity and maintaining, monitoring agricultural farms and creating fewer people involvement. We have demonstrated how IoT and Blockchain systems may be linked with agriculture’s intelligent component to maximize benefits for farmers. Security essential not only for the resources but also essential for agricultural products need to be protected and protected in the first instance, as protection from rodents and pests in the large agricultural field or grain shops. As a result, these problems need to be addressed. So, we designed an IoT and Blockchain based Smart Agriculture monitoring and Blockchain oriented Intelligence Security systems for Smart Agriculture Infrastructure.
Sukrutha L. T. Vangipuram, Saraju P. Mohanty, Elias Kougianos, Chittaranjan Ray
It is a known fact that large quantities of farm and meat products rot and are wasted if correct actions are not taken, which may lead to serious health issues if consumed. There is no proper system for tracking and communicating the status of the goods to their respective stakeholders in a secure way. Consumers have every right to know the quality of the products they consume. Using monitoring tools, such as the Internet of Agricultural Things (IoAT), and modern data protection techniques for storing and sharing, will help mitigate data integrity issues during the transmission of sensor records, increasing the data quality. The visibility state at the customer end is also improved, and they are aware of the agricultural product's conditions throughout the real-time distribution process. In this paper, we developed and implemented a CorDapp application to manage the data for the supply chain, called "agroString". We collected the temperature and humidity data using IoAT-Edge devices and various datasets from multiple sources. We then sent those readings to the CorDapp agroString and successfully shared them among the relevant parties. With the help of a Corda private blockchain, we attempted to increase data integrity, trust, visibility, provenance, and quality at each logistic step, while decreasing blockchain and central system limitations.
Support for sustainable smallholder farming has long been recognized as a key to healthy and resilient food production. The ideal situation – a global community of geographically dispersed smallholders enmeshed in local economies, thereby reducing waste – is incompatible with the centralizing forces currently dominating development. One need only view the COVID�19 pandemic and associated supply chain breakdowns to see the weakness of an overly connected global food system rife with perverse incentives, namely the centralizing nature of specialization and industrialization. Crop insurance is a form of proactive disaster risk management used to diffuse risks to agricultural production across space and time with other producers. It is a form of support that countries have long endeavored to implement so that farmers avoid turning to suboptimal traditional risk coping mechanisms. Notwithstanding, traditional insurance programs have been plagued by well-documented challenges creating a severe gap in service offerings, especially among smallholders in the developing world. As climate change raises agricultural risks through heightened uncertainty, it is increasingly necessary to augment the security of smallholder farms through closing the coverage gap. Fortunately, recent technological advancements have improved the prospect of overcoming barriers to reaching smallholders. Combining the decreasing cost and increasing sophistication of remote sensing and satellite technology with smart contracts and other innovations enabled by distributed ledger technology has the potential address many of the challenges of traditional insurance provision. Blockchain technology affords this potential through providing architecture to reduce transaction costs, increase trust and access, and deepen opportunities for reinsurance. The transparency and immutability of blockchain engenders a unique coordinating capability that allows for benefits superior to other organizing instruments. Despite limitations concerning the current state and maturity of blockchain technology, the pace and direction of development offer promise for near-term composability with key systems and functionality. This research uses a literature review to trace historical challenges in providing crop insurance and analyzes the opportunity for blockchain to mitigate them. It focuses on evaluating the potential to bolster the provision and uptake of a particular type of crop insurance – index�based microinsurance – through the combination of blockchain technology and public-private partnerships. The aim is to provide an analysis of how blockchain applications can improve existing crop microinsurance schemes and a guideline for how public-private partnerships should be organized to optimize implementation. Furthermore, this research holds in mind the ultimate goal of creating true at cost peer-to-peer index-based crop insurance. That is, after initial investment, coordination, and monitoring by a public-private partnership to overcome startup barriers, it is possible, and optimal, to create new regional smallholder insurance regimes running on decentralized infrastructure.
Rania A. Ahmed, Ezz El‐Din Hemdan, Walid El‐Shafai, Zeinab A. Ahmed · 6 authors
Abstract The Internet of Things (IoT) is an important technology that provides efficient and dependable solutions in a variety of domains, such as smart agriculture and climatic change. It integrates billions of smart devices that can communicate with one another and gives solutions to automatically maintain and monitor smart agricultural and environmental fields. The combination of IoT, Artificial Intelligence (AI), and blockchain technology will allow us to transform smart agriculture into the Internet of smart agriculture, providing greater control, management, and security in supply‐chain networks. This paper presents an overview of the technologies in the domains of IoT, Climate‐Smart Agriculture (CSA), AI, Machine Learning (ML), and blockchain. In addition, the paper presents several approaches for integrating IoT with CSA data analysis. Both AI and blockchain are adopted for efficient CSA systems. The paper is concerned with the combination of three recent technologies: IoT, ML, and blockchain to serve the CSA applications. The challenges and opportunities of combining these technologies to serve CSA are also discussed in the paper.
The Internet of Things (IoT) has rapidly progressed in recent years and immensely influenced many industries in how they operate. Consequently, IoT technology has improved productivity in many sectors, and smart farming has also hugely benefited from the IoT. Smart farming enables precision agriculture, high crop yield, and the efficient utilization of natural resources to sustain for a longer time. Smart farming includes sensing capabilities, communication technologies to transmit the collected data from the sensors, and data analytics to extract meaningful information from the collected data. These modules will enable farmers to make intelligent decisions and gain profits. However, incorporating new technologies includes inheriting security and privacy consequences if they are not implemented in a secure manner, and smart farming is not an exception. Therefore, security monitoring is an essential component to be implemented for smart farming. In this paper, we propose a cloud-enabled smart-farm security monitoring framework to monitor device status and sensor anomalies effectively and mitigate security attacks using behavioral patterns. Additionally, a blockchain-based smart-contract application was implemented to securely store security-anomaly information and proactively mitigate similar attacks targeting other farms in the community. We implemented the security-monitoring-framework prototype for smart farms using Arduino Sensor Kit, ESP32, AWS cloud, and the smart contract on the Ethereum Rinkeby Test Network and evaluated network latency to monitor and respond to security events. The performance evaluation of the proposed framework showed that our solution could detect security anomalies within real-time processing time and update the other farm nodes to be aware of the situation.