In a recent LinkedIn post, Anthony Butler, senior advisor to Saudi Central Bank ( SAMA) an expert in Blockchain and digital assets, called for DLT ( Distributed Ledger Experts) or Blockchain experts, as well as AI ( Artificial Intelligence), Machine Learning and software engineers to apply for positions in some world class projects in KSA.

According to Butler there are exciting opportunities in KSA. He states, “There are some world class projects that have an impact in KSA.”

In June 2023, Butler had made a similar call for talents for blockchain, AI and digital assets experts for jobs in KSA. At the time he mentioned roles for software engineers with experience working with DLT protocols and applications. According to Butler the role required experience implementing solutions using tech such as Ethereum, Hyperledger Besu, Hyperledger Fabric, and/or R3 Corda.”

KSA has been launching and investing in digital economy projects across the country.

They had launched a nationwide CBDC project in 2022 which is still underway.

In addition last week, KSA based Marhaba Blockchain Information Systems (MRHB) a blockchain web3 Infrastructure,  partnered with Saudi Arabia’s Digital Economy Centre (DEC)  an institution driving the digital transformation of Saudi Arabia’s economy in alignment with Vision 2030. The collaboration focuses on Blockchain, DLT and Artificial Intelligence (AI), initiatives.

Even Saudi Arabia’s Muqassa, a subsidiary of Saudi’s Tadawul Group, specialized in settlement of trades, signed an MOU (Memorandum of Understanding) with Swiss Blockchain enabled Instimatch, a cash management platform for institutions across industries and geographies to interconnect. The MOU will work to launch a repo trading platform to enhance the financial structure of the Saudi Capital Market.

Blockchain enabled entities such as Crysp Farms, a UAE based innovator and operator of decentralized blockchain enabled vertical farms, secured a $2.25 million ‘Pre-Series A’ round structured and led by Gate Capital with participation from regional investors, including those from the UAE and Saudi Arabia.

Additionally AI and Blockchain enabled Tribal Credit, founded by Egyptian entrepreneurs, will be expanding into Saudi Arabia, and using a renewed and increased debt facility of $150 million with Partners for Growth.

Swiss based The Hashgraph Association (THA), for Blockchain DLT digital enablement signed a strategic partnership with the Ministry of Investment of Saudi Arabia (MISA) to launch a “DeepTech Venture Studio” in Riyadh worth $250M USD over five years (2024-2028).

Blockchain has even infiltrated the LEAP 2024 Tech Exhibition and Conference, taking place between March 4th-7th 2024, in Riyadh KSA. Already many blockchain and DLT entities have announced their participation at the event, including names such as Antematter, who specialize in crafting cost-effective, innovative solutions in AI, Blockchain, and Cloud Development, iBLOCKCHAIN, who are fostering blockchain adoption across governments, enterprises, and the public sphere,  and companies such as BitWits, will be showcasing their web game, blockchain, and AI development.

So it would seem that KSA is definitely becoming a blockchain, DLT, and digital economy hub.

Saudi Imam Abdulrahman Bin Faisal University department of computer Science and Saudi Aramco Cybersecurity chair, published in MDPI a study for a solution for Smart Flood Detection to save lives using the integration of AI (Artificial Intelligence), Blockchain and drones.

According to the study, floods pose a serious risk and require immediate management and strategies for optimal response times. The Saudi city of Mecca has been impacted by climate change in the last decade as floods have increased despite the city’s location in the Arabian Gulf, which has a hot and wet climate. According to the General Authority for Statistics in Mecca, since 2010, the average peak rainfall has increased by 350%. Mecca experienced torrential rains on 23 December 2022, at least partly because of its location, surrounded by mountains, causing numerous vehicles to be swept away.

The authors propose a secure method of flood detection in Saudi Arabia using a Flood Detection Secure System (FDSS) based on deep active learning (DeepAL) based classification model in federated learning to minimize communication costs and maximize global learning accuracy.

As per their abstract, “We use blockchain-based federated learning and partially homomorphic encryption (PHE) for privacy protection and stochastic gradient descent (SGD) to share optimal solutions. Utilizing images and IoT data, FDSS can train local models that detect and monitor floods. The proposed FDSS enabled us to estimate the flooded areas and track the rapid changes in dam water levels to gauge the flood threat. This study concludes with a discussion of the proposed method and its challenges in managing floods in remote regions using artificial intelligence and blockchain technology.

The study introduces a drone application that uses blockchain to manage flooding in remote regions safely and in real-time. The framework can be helpful in missions based on both blockchain and IPFS. The proposed architecture of system nodes makes the process more secure by preventing information from being manipulated and enhancing the data analysis capability within the management system. In a blockchain network, the text data is recorded as part of the transaction information that is recorded during transactions. In addition, a visualization platform will allow access to transaction data, making it easier for operators to supervise their operations.

The study offers a scheme that improves the FL system performance by using DeepAL to select the optimal edge nodes and integrating the learned model parameters into a blockchain-based FL scheme to enhance the reliability and security of the FL system. This method is combined with modern cryptography techniques, such as homomorphic encryption, to achieve a high level of privacy and security capabilities.

In natural disasters, UAVs’ real-time data acquisition can prevent harm by controlling operations efficiently. They can be used to obtain aerial photographs and read water levels, wind speeds, and water speeds to predict weather events, prevent disasters, and aid rescues. These complex interactions can be achieved using AI, the computer-based system that executes tasks requiring intelligence.

With AI and machine learning, systems will be able to resist new, sophisticated attacks with shifting characteristics. Drones must be built with a collective machine-learning model integrating all data from IoT devices and webcams that can be sent to the MEC to create an algorithm with strong predictive capability.

The proposed framework assumes that UAVs collect data and MEC servers store it in the blockchain. This includes basic data, such as the device name, MAC address and type, and geographic data, such as latitude and longitude that help MEC servers acquire data. Before data is added to the blockchain, MEC servers verify UAV validity.

The study utilizes the Internet of Drones (IoD) which can help to save many lives during floods and other catastrophic weather events in places that are difficult for people to reach. IoT devices can be used to collect data on the location and status of people in the affected areas, such as their vital signs, to prioritize rescue efforts.

The data will be sent to a central server where deep-learning algorithms will be used to analyze the data and create a rescue plan. The plan will be sent to relevant organizations involved in the rescue efforts, allowing them to provide aid quickly and efficiently to those in need.

In conclusion the study believes that the system has the potential to significantly improve the efficiency and effectiveness of rescue efforts in disaster situations. By utilizing AI, blockchain, and IoT technologies, the system can quickly analyze large amounts of data and provide a comprehensive rescue plan, ultimately saving more lives.