Application of Artificial Intelligence in IoT Security for Crop Yield Prediction

This research explores the application of Artificial Intelligence (AI) in the Internet of Things (IoT) for crop yield prediction in agriculture. IoT devices, like sensors and drones, collect data on temperature, humidity, soil moisture, and crop health. AI algorithms process and integrate this data to provide a comprehensive view of the agricultural environment.AI-driven anomaly detection helps identify threats to crop yield, such as pests, diseases, and adverse weather conditions. Predictive analytics, based on historical and real-time data, forecast crop yield for informed decision-making in irrigation and fertilization.AI-powered image recognition detects early signs of pests and diseases, aiding timely treatment to prevent crop losses. Resource optimization allocates water and fertilizers efficiently, minimizing waste and environmental impact.AI-driven decision support systems offer personalized recommendations for ideal planting schedules and crop rotations, maximizing yield. Autonomous farming integrates AI into machinery for precision tasks like planting and monitoring.Secure communication protocols protect sensitive agricultural data from cyber threats, ensuring data integrity and privacy

Genetic algorithm for holistic VNF-mapping and virtual topology design

Producción CientíficaNext generation of Internet of Things (IoT) services imposes stringent requirements to the future networks that current ones cannot fulfill. 5G is a technology born to give response to those requirements. However, the deployment of 5G is also accompanied by profound architectural changes in the network, including the introduction of technologies like multi-access edge computing (MEC), software defined networking (SDN), and network function virtualization (NFV). In particular, NFV poses diverse challenges like virtual network function (VNF) placement and chaining, also called VNF-mapping. In this paper, we present an algorithm that solves VNF-placement and chaining in a metro WDM optical network equipped with MEC resources. Therefore, it solves the VNF-mapping in conjunction with the virtual topology design of the underlying optical backhaul network. Moreover, a version of the method providing protection against node failures is also presented. A simulation study is presented to show the importance of designing the three problems jointly, in contrast to other proposals of the literature that do not take the design of the underlying network into consideration when solving that problem. Furthermore, this paper also shows the advantages of using collaboration between MEC nodes to solve the VNF-mapping problem and the advantage of using shared protection schemes. The new algorithm outperforms other proposals in terms of both service blocking ratio, and number of active CPUs (thus reducing energy consumption). Finally, the impact of deploying different physical topologies for the optical backhaul network is also presented.Ministerio de Economía, Industria y Competitividad (grant TEC2017-84423-C3-1-P)Ministerio de Industria, Comercio y Turismo (grant BES 2015-074514)Spanish Thematic Network (contract RED2018-102585-T)INTERREG V-A España-Portugal (POCTEP) program (project 0677_DISRUPTIVE_2_E

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security