Follow blockchain research across journals, conferences, and preprint repositories.
6 results · page 1 of 1
Tommy Zhang
A new approach to influence longetivity of crops in a humid and heated area by bitcoin computers aimed to reduce greenhouse emmisions while sustaining food for all.
Béthel Atohoun, A. Charbel Atihou, Mikaël A. Mousse, Mithelle M. J. Alavo
To overcome the structural limitations of traditional hydroponic systems—inefficient input management, lack of verifiable traceability, high energy consumption, and absence of adaptive optimization—this paper presents an innovative architecture that synergistically integrates Distributed Ledger Technology (DLT), Internet of Things (IoT), and Artificial Intelligence (AI) to optimize resource management in controlled hydroponic environments. The proposed architecture constitutes a hybrid DTL, IoT and IA system founded on six principles: radical distribution of trust, defense in depth, verifiable trust through cryptographic proofs, modularity, native interoperability, and scalability. It comprises a distributed intelligent sensor network, a low-cost edge computing cluster, optimized artificial intelligence modules, and a DLT infrastructure based on Hyperledger Fabric with Raft consensus. Experimental results, obtained through system simulation on a 100 m² greenhouse and validated by partial prototyping, demonstrate robust operational performance: average latency of 847 ms from sensor to blockchain, throughput of 150 transactions per second, availability of 99.7%, support for 500 simultaneous sensors, and energy autonomy of 14 months. AI models achieve 96.3% accuracy in nutritional prediction, with pH prediction error of 0.08 units and EC error of 15 µS/cm. DDPG orchestration converges after 45 days with stabilization of the reward function. Comparative analysis reveals significant advantages: 18% yield increase, 15% reduction in input costs, 22% decrease in energy consumption during peak pricing periods, and 40% improvement in total cost of ownership over 5 years.
Wei‐Han Chen, Fengqi You
No abstract is available for this record.
Atif Rizwan, Anam Nawaz Khan, Muhammad Ibrahim, Rashid Ahmad · 6 authors
No abstract is available for this record.
Ling Zhang, Wang Xiujuan, Haoyu Wang, Jing Hua · 6 authors
This work explores the path to the convergence of virtual and real-world plants under the context of the metaverse. A mobile application named MetaPlant has been designed to offer a platform for learning about planting experiences. The application simulates the development and growth of individual plants based on the GreenLab model. It incorporates various features including the simulations of virtual fields and environmental conditions, the interactions with virtual plants, the visualization of plants using OpenGL, and user-to-user communications through the friend and community systems. This work can potentially integrate virtual and real-world farming practices using Internet of Things (IoT) technologies, produce digital products through Decentralized Autonomous Organization (DAO), and promote sustainable farming practices and knowledge sharing within a vibrant virtual farming community.
Nima Asgari, Matthew T. McDonald, Joshua M. Pearce
Greenhouses extend growing seasons in upper latitudes to provide fresh, healthy food. Costs associated with carbon-emission-intensive natural gas heating, however, limit greenhouse applications and scaling. One approach to reducing greenhouse heating costs is electrification by using waste heat from cryptocurrency miners. To probe this potential, a new quasi-steady state thermal model is developed to simulate the thermal interaction between a greenhouse and the environment, thereby estimating the heating and cooling demands of the greenhouse. A cryptocurrency mining system was experimentally evaluated for heating potential. Using these experimental values, the new thermal model was applied to the waste heat of the three cryptocurrency mining systems (1, 50, and 408 miners) for optimally sized greenhouses in six locations in Canada and the U.S.: Alberta, Ontario, Quebec, California, Texas, and New York. A comprehensive parametric study was then used to analyze the effect of various parameters (air exchange rate, planting area, lighting allowance factor, and photoperiod) on the thermal demands and optimal sizing of greenhouses. Using waste heat from cryptocurrency mining was found to be economically profitable to offset natural gas heating depending on the utility rates and Bitcoin value in a wide range of scenarios.