# AgriSecure: A Fog Computing-Based Security Framework for Agriculture 4.0 via Blockchain
## 2 Overview of Agriculture 4.0
### IoT in Agriculture 4.0  
Table 1 lists several well-known uses of IoT integration and utilization in agriculture.  
Intelligent soil cultivation system: This system would plow, weed, prepare the seedbed, and sow the field soil in order to prepare it for harvest.  
Efficient irrigation mechanisms: This technology would automate the controlled artificial supply of water needed for plant growth.  
Smart fertilizer systems: These automate the application of fertilizer to a field while allowing for precise control over the kind, amount, and timing of fertilizer.  
Intelligent pest detection and treatment systems: These systems keep an eye out for pest infestations, analyze agricultural damage, and incorporate methods to manage the infestation.  
Intelligent livestock agriculture: This involves employing cutting-edge technologies to breed animals and uses precision agriculture to enhance the quantity and quality of the produce.  
Smart harvesting system: This system harvests a field effectively by using IoT-based methods.  
Smart farm management system: This kind of technology would aim to offer analytics on data to increase field productivity and yield.  
Intelligent groundwater quality management system: The final product is greatly influenced by the quantity and quality of the groundwater. As a result, this system uses IoT approaches to maintain appropriate groundwater levels.  
Though there are many smart agriculture alternatives, they are still underdeveloped and offer a low degree of intellect. Many initiatives are limited in their automated systems, with the internet of things sending data to the base station [53]. There is also no implementation with the Internet in several cases, except that in a few cases, data is stored in the cloud by the local systems.  
The multi-layer architecture of IoT used in agriculture 4.0 consists of four layers, which are the physical layer, network layer, edge layer, and application layer. Table 2 below gives a detailed description of Resources used in the multi-layered architecture of IoT in Agriculture 4.0 [54].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Area** & **Years** & **Studies** \\ \hline Intelligent soil cultivation system & (2018–2023) & [22; 23; 24; 25; 26] \\ \hline Efficient irrigation mechanisms & (2019–2023) & [27; 28; 29; 30] \\ \hline Smart fertilizer systems & (2018–2023) & [31; 32; 33] \\ \hline Intelligent pest detection and treatment systems & (2018–2021) & [34; 35; 36] \\ \hline Intelligent livestock agriculture & (2021–2022) & [37; 38; 39; 40] \\ \hline Smart harvesting system & (2019–2020) & [41; 42; 43; 44] \\ \hline Smart farm management system & (2018–2021) & [45; 46; 47] \\ \hline Intelligent groundwater quality management system & (2018–2022) & [48; 49; 50; 51; 52] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Use of IoT in agriculture and corresponding studies.  
The RFID, cameras, actuators, GPS, and all these devices are all implemented in the physical layer, which collects data from the farming field and digitizes them using an Analog to Digital converter (ADC). As the equipment at the physical layer does not compute and store the data, this needs to connect with the edge layer through the network layer. The edge layer includes various resources such as decision-making, gateway, data filters, data security, and interfaces [55].  
The advancement of devices and technological developments will allow for the incorporation of more computer capabilities into systems. This type of integration aims to meet the various needs of agricultural mechanization, farming techniques, and sustainable agriculture [56; 57]. A further issue is data security. This is very important to focus on data privacy, the trustworthiness of data, and the correctness of data from generation to decision-making.