From Industry 4.0 to Agriculture 4.0: Current Status, Enabling Technologies, and Research Challenges

The three previous industrial revolutions profoundly transformed agriculture industry from indigenous farming to mechanized farming and recent precision agriculture. Industrial farming paradigm greatly improves productivity, but a number of challenges have gradually emerged, which have exacerbated in recent years. Industry 4.0 is expected to reshape the agriculture industry once again and promote the fourth agricultural revolution. In this article, first, we review the current status of industrial agriculture along with lessons learned from industrialized agricultural production patterns, industrialized agricultural production processes, and the industrialized agri-food supply chain. Furthermore, five emerging technologies, namely the Internet of Things, robotics, artificial intelligence, big data analytics, and blockchain, toward Agriculture 4.0 are discussed. Specifically, we focus on the key applications of these emerging technologies in the agricultural sector and corresponding research challenges. This article aims to open up new research opportunities for readers, particularly industrial practitioners.

[1]  M. Rapela Fostering Innovation for Agriculture 4.0: A Comprehensive Plant Germplasm System , 2019 .

[2]  K. Otsuka,et al.  Why African rural development strategies must depend on small farms , 2016 .

[3]  David Ball,et al.  Farm Workers of the Future: Vision-Based Robotics for Broad-Acre Agriculture , 2017, IEEE Robotics & Automation Magazine.

[4]  Lei Shu,et al.  Security and Privacy for Green IoT-Based Agriculture: Review, Blockchain Solutions, and Challenges , 2020, IEEE Access.

[5]  S. Wolfert,et al.  Big Data in Smart Farming – A review , 2017 .

[6]  Guan Gui,et al.  Deep Learning Based Improved Classification System for Designing Tomato Harvesting Robot , 2018, IEEE Access.

[7]  Nadeem Javaid,et al.  Blockchain-Based Agri-Food Supply Chain: A Complete Solution , 2020, IEEE Access.

[8]  Evan D. G. Fraser,et al.  Opportunities and Challenges for Big Data in Agricultural and Environmental Analysis , 2018, Annual Review of Resource Economics.

[9]  Eryk Dutkiewicz,et al.  Proof-of-Stake Consensus Mechanisms for Future Blockchain Networks: Fundamentals, Applications and Opportunities , 2019, IEEE Access.

[10]  Fei Tao,et al.  Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison , 2018, IEEE Access.

[11]  Junyu Wang,et al.  Food Safety Traceability System Based on Blockchain and EPCIS , 2019, IEEE Access.

[12]  Fernando Auat Cheein,et al.  Human–robot interaction in agriculture: A survey and current challenges , 2019, Biosystems Engineering.

[13]  Tianjian Chen,et al.  Federated Machine Learning: Concept and Applications , 2019 .

[14]  Jiabin Yu,et al.  Blockchain-Based Safety Management System for the Grain Supply Chain , 2020, IEEE Access.

[15]  Hyoung Il Son,et al.  Modeling and Control of Heterogeneous Agricultural Field Robots Based on Ramadge–Wonham Theory , 2020, IEEE Robotics and Automation Letters.

[16]  S. Andrew Gadsden,et al.  An overview of autonomous crop row navigation strategies for unmanned ground vehicles , 2019, Engineering in Agriculture, Environment and Food.

[17]  Ismo Hakala,et al.  Effects of temperature and humidity on radio signal strength in outdoor wireless sensor networks , 2015, 2015 Federated Conference on Computer Science and Information Systems (FedCSIS).

[18]  P. Craufurd,et al.  Gender differentiated small-scale farm mechanization in Nepal hills: An application of exogenous switching treatment regression , 2020, Technology in society.

[19]  Lammert Kooistra,et al.  Fast Classification of Large Germinated Fields Via High-Resolution UAV Imagery , 2019, IEEE Robotics and Automation Letters.

[20]  Grzegorz Cielniak,et al.  Analysis of Morphology-Based Features for Classification of Crop and Weeds in Precision Agriculture , 2018, IEEE Robotics and Automation Letters.

[21]  Yuan He,et al.  From Surveillance to Digital Twin: Challenges and Recent Advances of Signal Processing for Industrial Internet of Things , 2018, IEEE Signal Processing Magazine.

[22]  N. Guiomar,et al.  Typology and distribution of small farms in Europe: Towards a better picture , 2018, Land Use Policy.

[23]  D. Heederik,et al.  Impacts of Intensive Livestock Production on Human Health in Densely Populated Regions , 2017, GeoHealth.

[24]  Fadel Adib,et al.  Networking across boundaries: enabling wireless communication through the water-air interface , 2018, SIGCOMM.

[25]  Mukesh K. Mohania,et al.  Internet of Blockchains: Techniques and Challenges Ahead , 2018, 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[26]  Mohammed Samaka,et al.  Security Services Using Blockchains: A State of the Art Survey , 2018, IEEE Communications Surveys & Tutorials.

[27]  Jean-Pierre Belaud,et al.  Big data for agri-food 4.0: Application to sustainability management for by-products supply chain , 2019, Comput. Ind..

[28]  J. Alex Thomasson,et al.  A review of the state of the art in agricultural automation. Part III: Agricultural machinery navigation systems , 2018 .

[29]  Ricardo Carelli,et al.  Agricultural Robotics: Unmanned Robotic Service Units in Agricultural Tasks , 2013, IEEE Industrial Electronics Magazine.

[30]  Massimo Vecchio,et al.  Blockchain-based traceability in Agri-Food supply chain management: A practical implementation , 2018, 2018 IoT Vertical and Topical Summit on Agriculture - Tuscany (IOT Tuscany).

[31]  David Kelton,et al.  Recent advancement in biosensors technology for animal and livestock health management. , 2017, Biosensors & bioelectronics.

[32]  Rakesh D. Raut,et al.  Enabling Technologies for Industry 4.0 Manufacturing and Supply Chain: Concepts, Current Status, and Adoption Challenges , 2020, IEEE Engineering Management Review.

[33]  Man Zhang,et al.  Development of a following agricultural machinery automatic navigation system , 2019, Comput. Electron. Agric..

[34]  Nathalie Mitton,et al.  Denial-of-Sleep Attacks against IoT Networks , 2019, 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT).

[35]  Hod Lipson,et al.  Additive manufacturing for the food industry , 2015 .

[36]  James W. Peltier,et al.  Digital information flows across a B2C/C2C continuum and technological innovations in service ecosystems: A service-dominant logic perspective , 2020, Journal of Business Research.

[37]  Lucas Santos Dalenogare,et al.  Industry 4.0 technologies: Implementation patterns in manufacturing companies , 2019, International Journal of Production Economics.

[38]  Tristan Perez,et al.  Peduncle Detection of Sweet Pepper for Autonomous Crop Harvesting—Combined Color and 3-D Information , 2017, IEEE Robotics and Automation Letters.

[39]  Roland Siegwart,et al.  AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming , 2018, IEEE Robotics and Automation Letters.

[40]  Qassim Nasir,et al.  Inter Blockchain Communication: A Survey , 2019, ArabWIC 2019.

[41]  Ye Liu,et al.  EcoVibe: On-Demand Sensing for Railway Bridge Structural Health Monitoring , 2019, IEEE Internet of Things Journal.

[42]  Yael Edan,et al.  Automatic Adjustable Spraying Device for Site-Specific Agricultural Application , 2018, IEEE Transactions on Automation Science and Engineering.

[43]  S. Brodt,et al.  Feasibility and sustainability of agroforestry in temperate industrialized agriculture: preliminary insights from California , 2019, Renewable Agriculture and Food Systems.

[44]  Fumiya Iida,et al.  Achieving Robotically Peeled Lettuce , 2018, IEEE Robotics and Automation Letters.

[45]  Fan Yang,et al.  Poster: Photovoltaic Agricultural Internet of Things the Next Generation of Smart Farming , 2019, EWSN.

[46]  Suresh Neethirajan,et al.  Recent advances in wearable sensors for animal health management , 2017 .

[47]  Luca Mottola,et al.  Synchronous Transmissions in Low-Power Wireless , 2020, ACM Comput. Surv..

[48]  A. Colantoni,et al.  Revolution 4.0: Industry vs. Agriculture in a Future Development for SMEs , 2019, Processes.

[49]  Chee Yen Leow,et al.  An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges , 2018, IEEE Internet of Things Journal.

[50]  J. Mellor,et al.  The Impact of Growth in Small Commercial Farm Productivity on Rural Poverty Reduction , 2017 .

[51]  A. Komarek,et al.  A review of types of risks in agriculture: What we know and what we need to know , 2020 .

[52]  Cyrill Stachniss,et al.  Fully Convolutional Networks With Sequential Information for Robust Crop and Weed Detection in Precision Farming , 2018, IEEE Robotics and Automation Letters.

[53]  R. Suman,et al.  Industry 4.0 technologies and their applications in fighting COVID-19 pandemic , 2020, Diabetes & Metabolic Syndrome: Clinical Research & Reviews.

[54]  Giulio Reina,et al.  A Survey of Ranging and Imaging Techniques for Precision Agriculture Phenotyping , 2017, IEEE/ASME Transactions on Mechatronics.

[55]  F. Loreto,et al.  Opportunities and Limitations of Crop Phenotyping in Southern European Countries , 2019, Front. Plant Sci..

[56]  Janusz Kacprzyk,et al.  Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture , 2020, Comput. Ind..

[57]  Junhu Ruan,et al.  Agriculture IoT: Emerging Trends, Cooperation Networks, and Outlook , 2019, IEEE Wireless Communications.

[58]  Benjamin Fernandez,et al.  A Simplified Optimal Path Following Controller for an Agricultural Skid-Steering Robot , 2019, IEEE Access.

[59]  Ali Mansour,et al.  Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk , 2019, IEEE Access.

[60]  James Brown,et al.  TempLab: A testbed infrastructure to study the impact of temperature on wireless sensor networks , 2014, IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks.

[61]  Thilo Steckel,et al.  Farming in the Era of Industrie 4.0 , 2018 .

[62]  Hyoung Il Son,et al.  Unmanned Aerial Vehicles in Agriculture: A Review of Perspective of Platform, Control, and Applications , 2019, IEEE Access.

[63]  M. Weiss,et al.  Remote sensing for agricultural applications: A meta-review , 2020 .

[64]  Min Chen,et al.  Analyzing the trend of O2O commerce by bilingual text mining on social media , 2019, Comput. Hum. Behav..

[65]  Yasuhiro Hayashi,et al.  Machine Learning Approach for Graphical Model-Based Analysis of Energy-Aware Growth Control in Plant Factories , 2019, IEEE Access.

[66]  Shintaro Shinjo,et al.  A GaN PA for 4G LTE-Advanced and 5G: Meeting the Telecommunication Needs of Various Vertical Sectors Including Automobiles, Robotics, Health Care, Factory Automation, Agriculture, Education, and More , 2017, IEEE Microwave Magazine.

[67]  Roland Siegwart,et al.  weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming , 2017, IEEE Robotics and Automation Letters.

[68]  Yi-Bing Lin,et al.  AgriTalk: IoT for Precision Soil Farming of Turmeric Cultivation , 2019, IEEE Internet of Things Journal.

[69]  Paolo Valigi,et al.  Weakly Supervised Fruit Counting for Yield Estimation Using Spatial Consistency , 2019, IEEE Robotics and Automation Letters.

[70]  Ranveer Chandra,et al.  Towards Low Cost Soil Sensing Using Wi-Fi , 2019, MobiCom.

[71]  Kay Römer,et al.  Impact of Temperature Variations on the Reliability of LoRa - An Experimental Evaluation , 2018, SENSORNETS.

[72]  Madhur Gautam,et al.  Too Small to Be Beautiful?: The Farm Size and Productivity Relationship in Bangladesh , 2018, Food Policy.

[73]  Pascal Neveu,et al.  Dealing with multi‐source and multi‐scale information in plant phenomics: the ontology‐driven Phenotyping Hybrid Information System , 2018, The New phytologist.

[74]  A. Reyes Yanes,et al.  Towards automated aquaponics: A review on monitoring, IoT, and smart systems , 2020 .

[75]  Jan Beutel,et al.  Thermoelectric Energy Harvesting From Gradients in the Earth Surface , 2020, IEEE Transactions on Industrial Electronics.

[76]  Hyeon Park,et al.  Smart Livestock Farms Using Digital Twin: Feasibility Study , 2018, 2018 International Conference on Information and Communication Technology Convergence (ICTC).

[77]  Pedro Ponce,et al.  Sensing, smart and sustainable technologies for Agri-Food 4.0 , 2019, Comput. Ind..

[78]  Charlie C. L. Wang,et al.  Plant Phenotyping by Deep-Learning-Based Planner for Multi-Robots , 2019, IEEE Robotics and Automation Letters.

[79]  T. Pridmore,et al.  Plant Phenomics, From Sensors to Knowledge , 2017, Current Biology.

[80]  B. Sturm,et al.  Implementation of machine vision for detecting behaviour of cattle and pigs , 2017 .

[81]  Debashis De,et al.  Internet of Things (IoT) for Smart Precision Agriculture and Farming in Rural Areas , 2018, IEEE Internet of Things Journal.

[82]  Hongyi Xu,et al.  Social commerce: A systematic review and data synthesis , 2018, Electron. Commer. Res. Appl..

[83]  Francisco Rovira-Más,et al.  From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management , 2020, Agronomy.

[84]  Giuseppe Aceto,et al.  A Survey on Information and Communication Technologies for Industry 4.0: State-of-the-Art, Taxonomies, Perspectives, and Challenges , 2019, IEEE Communications Surveys & Tutorials.

[85]  Joris IJsselmuiden,et al.  Robot navigation in orchards with localization based on Particle filter and Kalman filter , 2019, Comput. Electron. Agric..

[86]  Khaled Salah,et al.  Blockchain-Based Soybean Traceability in Agricultural Supply Chain , 2019, IEEE Access.

[87]  Victoria Beltran,et al.  Decision support systems for agriculture 4.0: Survey and challenges , 2020, Comput. Electron. Agric..

[88]  Gagandeep Kaur,et al.  Scalability in Blockchain: Challenges and Solutions , 2020, Handbook of Research on Blockchain Technology.

[89]  Amy Yau,et al.  A comparison of social media marketing between B2B, B2C and mixed business models , 2018, Industrial Marketing Management.

[90]  Kamran Abid,et al.  A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming , 2019, IEEE Access.

[91]  Ercan Öztemel,et al.  Literature review of Industry 4.0 and related technologies , 2018, J. Intell. Manuf..

[92]  David Mohaisen,et al.  Exploring the Attack Surface of Blockchain: A Comprehensive Survey , 2020, IEEE Communications Surveys & Tutorials.

[93]  I. Husti,et al.  The role of digitalization in the agricultural 4.0 – how to connect the industry 4.0 to agriculture? , 2018 .

[94]  Yang Lu,et al.  Industry 4.0: A survey on technologies, applications and open research issues , 2017, J. Ind. Inf. Integr..

[95]  Debashis Ghosh,et al.  Energy efficient mobile vision system for plant leaf disease identification , 2014, 2014 IEEE Wireless Communications and Networking Conference (WCNC).

[96]  Li Da Xu,et al.  Industry 4.0: state of the art and future trends , 2018, Int. J. Prod. Res..