# A Survey of Blockchain Applications for Management in Agriculture and Livestock Internet of Things
## 3 Challenges and Motivations
### Current Challenges in Agricultural and Livestock IoT  
With the swift advancement of IoT technologies in agriculture and livestock management, significant changes have been initiated in these sectors. These technologies have revolutionized farms into highly automated and intelligent systems, thus enhancing production efficiency and the efficacy of resource management. Nonetheless, these advancements also introduce a range of challenges in data management. Data Management:  
The expansive deployment of IoT in agriculture and livestock management generates vast datasets concerning crop growth, climate changes, soil quality, and animal health. Managing these data effectively is crucial for refining production processes, elevating harvest quality, and ensuring food safety. Firstly, the collection and storage of data present considerable challenges. Considering the volume and diversity of data, robust mechanisms are needed to maintain data integrity. Additionally, safeguarding data against corruption or tampering during transmission is vital for preserving its security and completeness. Secondly, the challenge of data sharing and network efficiency is pivotal in the context of agricultural and livestock IoT. Information processing can be adversely affected by high data transmission volumes due to network congestion and delays. Therefore, managing these data efficiently and deciding which portions to upload and share is critical for optimal network performance. Lastly, the challenges of data filtering and validity assessment are paramount. Identifying and extracting valuable data for insightful analysis and decision-making, given the constraints of limited resources, is essential. This necessitates sophisticated algorithms and analytical tools to distill the most relevant information from the extensive datasets for effective agricultural production and management. In conclusion, the data management challenges in agricultural and livestock IoT encompass but are not limited to maintaining the integrity of data collection and storage, ensuring network efficiency, and conducting data filtering and validity assessment. Addressing these challenges demands an integrated approach using advanced technologies, innovative methods, and collaborative strategies to achieve optimal data management. Security and Trustworthiness:  
The integration of IoT technology brings forth security and trust issues. Securing data against unauthorized access or manipulation and fostering trust among stakeholders is critical. The supply chain involves extensive data exchange and processing from raw material acquisition through processing and distribution to the end product. The security of these phases is crucial for the supply chain's reliability and efficiency, with data security and tamper resistance as primary concerns. Unauthorized access or tampering can disrupt the supply chain and affect its credibility. Cultivating trust among supply chain participants is also fundamental. Without trust, the exchange of critical information may be hindered, affecting efficiency. In an age of information surplus, finding valuable information and verifying its accuracy is essential for decision-making. Tackling these challenges requires a holistic approach, including technicalsafeguards, transparent communication, sophisticated data analysis techniques, and trust in the supply chain. Privacy Protection:  
With the widespread adoption of IoT systems in the agriculture and livestock sectors, safeguarding both commercial and personal information remains a pivotal concern. These systems collect extensive sensitive data--ranging from crop details and climatic patterns to soil conditions and livestock health--making robust data management essential for upholding farmers' privacy rights and protecting trade secrets. A key challenge lies in preventing unauthorized access and misuse of personal data, given that comprehensive datasets often include geographic locations, farming practices, and economic conditions.