# A Novel Edge Platform Streamlining Connectivity between Modern Edge Devices and the Cloud
###### Abstract
The evolution towards distributed DL with MEC, introduced by [16] through the BlockDeepEdge framework, represents a significant leap forward in securing and optimizing IoT devices. By facilitating secure, decentralized, and efficient DL operations, BlockDeepEdge addresses privacy and latency issues, enhancing real-time processing and decision-making capabilities at the network's edge. However, while BlockDeepEdge's methodology of distributed deep learning and blockchain provides robust data security and efficient processing, its decentralized nature may not fully cater to scenarios where seamless integration and synchronous operation between cloud and edge environments are crucial. In complex agricultural systems, where the synergy between cloud and edge computing is imperative for comprehensive data analysis and management, the requirement for a harmonized cloud-edge interaction highlights a critical consideration. Although BlockDeepEdge offers significant benefits in terms of security and localized decision-making, its application might be nuanced in contexts demanding intricate cloud-edge collaboration for optimal performance and data coherence across the IoT spectrum. These data, crucial for optimizing farm management and decision-making, as noted by [17], face the challenge of integration and effective use. The necessity for systematic evaluations, emphasized by [18], underlines the importance of leveraging technologies like Smart Farming and IoT. These technologies facilitate data-driven management to tackle complex challenges in agriculture, from enhancing crop yields to promoting sustainability. In agriculture, the influx of data from computational devices at the edge is transforming the sector. As the authors of [17] note, the challenge lies in integrating these data to enhance farm management and decision-making. Ref. [18] emphasizes the need for systematic evaluations in promoting sustainable farm systems, highlighting the role of Smart Farming and IoT in facilitating data-driven management. Real-time reconfiguration capabilities are crucial in agriculture for quick responses to changes like weather fluctuations or disease alerts. This involves enhancing traditional tools with autonomous context-awareness and remote-control capabilities, as discussed by [18]. The integration of robots and human analysis in a cyber-physical cycle is key to this evolution, as outlined by [10]. Refs. [2; 19] highlight the use of IoT in monitoring animal welfare, with technologies like Reproductive Management Systems improving livestock productivity. However, cloud-based solutions face challenges like connectivity and bandwidth, especially in remote farming areas. Edge computing emerges as a solution, reducing latency and bandwidth usage, and enhancing data privacy and sensor battery life. It allows for real-time decision-making, as exemplified in crop irrigation scenarios where sensors process data locally for immediate irrigation decisions. Cooperative frameworks like CoopEdge, introduced by [PERSON] et al. [20], leverage blockchain for secure and decentralized operations, while architectures proposed by [PERSON] et al. [21] ensure task reliability through comprehensive monitoring. Additionally, innovative data services discussed by [PERSON] et al. [22] facilitate efficient data handling in cooperative edge environments, underscoring edge computing's potential in real-time IoT applications. To manage the transport layer effectively, MQTT, a lightweight protocol ideal for machine-to-machine communication in IoT, was adopted, as described by [23; 24]. Ref. [25] provides a qualitative comparison with CoAP, suggesting MQTT's suitability for applications requiring advanced functionalities like message persistence and secure multicast. In summary, the interplay of edge and cloud computing, along with efficient transport protocols like MQTT, is reshaping data processing in industries such as agriculture, enhancing efficiency and enabling smarter, sustainable practices.