Thesis Changes - Systems Dynamics

The intricacy of the planet exceeds our grasp, no matter how amazing the human intellect is. Our cognitive models are restricted, incoherent, and untrustworthy. Our potential to comprehend the consequences of our actions as they occur is limited. We make judgments that seem logical in the near future and in our local context, but these choices sometimes backfire and harm us in the long term (Sterman, 2000). Therefore, study of the dynamics involved in the system is important.

Systems thinking equips individuals with the logic, concept, information, and abilities they require to identify the interconnections, changes that take place, frameworks, and mechanisms underneath complicated scenarios (Meadows, 2009). Systems thinking promotes ideas and resources to assist individuals perceive multiple viewpoints, evaluate preconceived ideas, discover architectural and operational links, shift factors, and transition procedures, and recognise the effect of environmental and societal elements (Fortmann-Roe & Bellinger, 2013). This paper is going to focus on those thinking for the application case of vehicle insurance and trust management. The idea with the application case is to involve blockchain, cloud computing, and Internet of Things in the research.

Blockchain is a decentralized digitized ledgers that are security conspicuous and resilient to tampering. They are generally deployed without a centralized authority. This is prompted not only by the fact that the best application of this technology is the blockchain-based cryptocurrency, but also by substantial process flaws and a big cost structure issue particular to this industry.

Cloud computing, on the other hand, provides nearly endless storage and processing capacity, allowing it to provide on-demand, efficient, and high-quality service for internet of things use cases. The convergence of cloud technology with IoT, in particular, paves the way for a new idea known as CoT, which has the potential to benefit both industries. Furthermore, the cloud's extensive capabilities are particularly beneficial to the Internet of Things, and its integration with IoT networks can help the cloud gain prominence in real-world applications. Furthermore, CoT has the potential to transform existing IoT service delivery architectures by requiring less administrative manpower, a high processing capacity, and excellent service availability.

The thesis is based on a study of the research conducted around the topic core and the formulation of a set of analytical observations, simulation, and modelling. It will further study the dynamics in order to construct an intentional systems architecture, its ramifications, and closing remarks of the research findings.

The prime objective of this thesis is to research about the blockchain technology involved in cloud computing. Because of its decentralized nature, transparency, and more security, many business applications are changing with time in cloud. The study also comprises of a system-dynamic model for blockchain technology on cloud. Therefore, this dissertation is analyzing an IoT application-based scenario of vehicle insurance and trust management using cloud based blockchain.

The sub-objectives of the thesis are:

1. Forming system integration architecture analysis for the information systems used in the selected cloud based and blockchain based IoT application.

2. Implementation recommendations of system dynamics model in cloud blockchain based IoT application.

The thesis is based on the analysis of the research performed around the topic core and formulating a set of analytical observations, and modelling. The research was carried out in order to make the best possible literature review for an IoT application-based scenario of vehicle insurance and trust management using cloud based blockchain.

The important section of literature review majorly involves exploration and deep understanding of the following parts:

· Exploration and Deliberate Secondary Research on Blockchain

· Understanding and exploring cloud of things

· Understanding the architecture of cloud integrated blockchain

· Vehicle insurance and trust management workarounds

· Working case scenarios for vehicle insurance and trust management

· Process diagram for vehicle insurance and trust management

· System elements for vehicle insurance and trust management

· Intel workaround instance for the system

In brief, the literature review provided the who idea about the architecture, process, and the systems involved in the targeted application-based scenario of vehicle insurance and trust management using cloud based blockchain.

The practical part of this dissertation is really a work of art. Creating the system dynamics model for the application, which is fairly unexplored, is made possible because of the systematic approach the author have adopted. The below are the main elements that the practical part is involving:

· Required factors to build a real-world system of the chosen application case

· Use case diagram for the cloud based blockchain application chosen for vehicle insurance and trust management

· Sequence diagram for the case

· Activity diagram for the case

· Figuring out quantitative variables involved in hazard score system for trust management

· Casual loop diagram for the case

· Stock and Flow diagram for the case

This way the practical part was completely formed by the author using the best system dynamics practices and tools needed. Because of the very complex case, the model is built based on the hazard score system as the system is involved as the main part of vehicle insurance and trust management system.

Based on the practical and theoretical part, recommendations were then formed. The recommendation specifically involves the recommendations for implementation of the system. Lastly, the dissertation is concluded with the overall viewpoint based on the dissertation.

Block chain technology is generating a lot of buzz and sparking a lot of initiatives across a variety of sectors. The money market, on the other hand, is considered as a key adopter of the blockchain idea. This is motivated not just by the reality that the greatest implementation of this technology is the blockchain - based Cryptocurrency, but also by significant process inadequacies and a major costs structure problem unique to this business (Nofer, et al., 2017). Furthermore, the economic meltdown proved that even in financial institutions, identifying the exact current holder of a commodity is often not achievable.

Blockchain is a decentralized digitized ledgers that are security conspicuous and resilient to tampering. They are generally deployed without a centralized authority. At its most basic stage, blockchain allow an organisation or individuals to log interactions in a public ledger within the same group, with the result that no event can be modified once it has been recorded while the blockchain infrastructure is operating normally (Quest, 2018).

The complexity of distributed ledger technology, as well as its heavy dependence on cryptographic building blocks and distributed networks, makes it difficult to grasp. Each element, on the other hand, may be simply explained and utilised as a block component to better comprehend the broader complicated system (Li, et al., 2022). After being validated and passing through a consensual process, each block is cryptographically connected to the one before it. Previous blocks become progressively challenging to change when more newer blocks are introduced. Fresh blocks are duplicated throughout network replicas of the ledger, and any disputes are handled immediately according to pre-determined procedures.

The technology of blockchain utilizes hash functions to operate. The blockchain is formed by a sequence of blocks, each of which contains the hash ferment of the preceding block's header. A new hash would be generated if an earlier conducted block was modified. As a result of including the preceding block's hash in future blocks, all following blocks will have distinct hashes (Yaga, et al., 2018). As a result, changed blocks may be easily detected and rejected.

Source : Yaga, et al., 2018

Merkle tree is a database model in which all of the information is hashed and concatenated until just one root hash reflects the whole structure. Just like the Merkle tree example illustrated in the next figure, the hashes are joined to each other and forming the whole component structure as one. This is what makes the blockchain technology distinctive, special, and secure.

Source: Yaga, et al., 2018

Conflicts cause separate copies of the blockchain to be created momentarily, as seen in figure ahead. These variations aren't "wrong," but rather reflect the knowledge accessible to each node at the time (Yaga, et al., 2018). Because the contending blocks are likely to include distinct transactions, people who have block n(A) may witness transactions of digital assets that aren't existent in block n (B). If the blockchain infrastructure involves bitcoin, it's possible that based upon what edition of the ledger is being examined, some blockchain currency will be expended and unused.

Source: Yaga, et al., 2018

In most cases, disagreements are handled swiftly. The majority of blockchain systems will await before the subsequent block is produced before recognising the lengthier chains as the legitimate chain (Murthy, et al., 2020). Because it received the next acceptable block, the blockchain holding block n(B) then becomes legitimate chain, as shown in Figure. Any transactions found in block n(A), the stranded block, but not in the block n(B) chain, is restored to the pending transactions bucket. Because the design does not have a centralized system, this list of pending transactions is stored individually at each node.

Source: Yaga, et al., 2018

Because blocks can be replaced, a transaction is normally not regarded as approved until a few subsequent blocks have been constructed on pinnacle of the block holding the pertinent transaction. Because blocks can be overridden, approval of a block is frequently stochastic instead of definitive. More the block stacked on pinnacle of a released block, the less likely the original block would be replaced.

Source: Nguyen & Ding, 2020

Because of its enormous capacity to create interesting solutions over a wide range of purposes, IoT has become a critical component of the forthcoming Internet and has attracted significant interest from academia and industry. IoT effectively integrates disparate equipment and things to produce a particular ecosystem in which sensing, analyzing, and transmission functions are carried out without the need for human intervention. Due to the limited processing and memory capacities of Internet of things, significant amounts of data created by a multitude of devices in existing IoT network pose a barrier in ensuring the appropriate Quality of the services also known as QoS.

Cloud technology, on the other hand, offers almost infinite storage and processing capacity, allowing it to deliver on-demand, efficient, and quality service for internet of things use cases. The confluence of cloud technology and IoT, in particular, opens the door to a new concept known as CoT, which may benefit both sectors. Furthermore, the cloud's vast capabilities are extremely advantageous to Internet of things, and its integration with Iot networks can help the cloud acquire more prominence in real-world applications. Furthermore, CoT has the potential to alter existing IoT service delivery architectures with little administration labor, high processing capacity, and high availability of services (Nguyen & Ding, 2020).

The graphic depicts the overall idea of CoT with a networking framework that includes IoT equipment, cloud technology, statistical solutions, and the application server. IoT systems are employed in this structure to detect and gather information from surrounding areas. IoT gadgets, on the other hand, will send captured information to the cloud for information gathering due to their restricted processing capacity. Cloud computing has the potential to give strong data computation and warehousing capabilities. Analytical solutions such as historical data tracking, data archiving, and scientific techniques can be given to facilitate Internet of things. The outputs of cloud data computation are utilized to support end programs, with the goal of making IoT service provisioning easier and meeting end users' needs.

Due to cloud computing's autonomous capacity provisioning possibilities, the CoT infrastructure enables provide immediate solutions to consumers everywhere and at any moment. It allows for the provision of automated services without the involvement of humans. CoT opens up new potential to boost IoT computing by facilitating information unloading and information execution distantly (Nguyen & Ding, 2020), thanks to cloud computing's limitless virtual computational power. This not only increases domestic gadget compute capability, but it also efficiently tackles IoT system challenges such as power conservation and connectivity conservation.

Furthermore, by employing network infrastructure, virtual PCs, and application architectures, CoT can deliver easier and autonomous IT administration and governance solutions. Consumers of the Network of Things may easily use clouds infrastructure to deliver functionalities without the requirement for deployment, calibration, or physical interaction. Moreover, the accessibility of cloud-based arrangement governance structures enables unrestrained communications and interconnectedness between Connected equipment, and between entities and users, empowering ubiquitous solutions and encouraging the stringent cooperative initiatives of multiple IoT eco - systems in the internet Infrastructure.

Source: Zou, et al., 2022

When blockchain, cloud, and IoT are combined, a new concept simply called BCoT emerges. The integration of these developing innovations offers significant advantages to each realm, piquing scholarly and industrial attention. In reality, there are a multitude of complimentary linkages between the blockchain and the Cloud of Things for potential implementation. Blockchain has been dubbed "Blockchain as a Service" in the field of cloud computing (Dorsala, et al., 2021). Blockchain can provide totally novel cloud storage services that are highly resilient to data changes by offering a decentralised repository infrastructure employing virtual memory nodes. Instead of depending on typical cloud storage facilities, blockchain joins computer nodes, such as cloud virtualized machines and external systems, to create a completely decentralised storage facility that does not require a centralized power.

The decentralised structure of blockchain makes it a potential solution for successfully solving capacity and potential collapse concerns in the CoT system by removing the need for a trustworthy third party. Furthermore, blockchain's design gives all internet users with equivalent validating powers to validate IoT information accuracy and authenticity.

Blockchain allows many parties to collaborate in a novel way, having infinite information exchange possibilities and no need to be afraid of trustworthiness. The absence of the 3rd party aids in the creation of transparent ecosystems in which any entities and cloud service providers with an expertise in the platform may join and cooperate to accomplish the platform's shared objectives.

The BCoT solution may focus on providing reliable authentication and authorization by utilising blockchain consensus protocol, which allows cloud service providers and Internet of things equipment to autonomously approve all actions, preventing possible risks to cloud assets and enhancing the management over IoT information. Furthermore, the blockchain allows customers to follow their activities throughout the system, allowing them to preserve equipment and information possession while also increasing data confidentiality.

Cloud computing can aid in the replication of blockchain content over a channel of processing systems linked together via cooperative clouds. This reduces the danger of a single-point-of-failure owing to the loss of any cloud nodes, ensuring that services remain available. Furthermore, the inter-cloud environment can allow the blockchain network to continue to function even if one of the cloud servers is attacked.

The volume of interactions in blockchain infrastructure can be massive in humongous blockchain technologies. As a result, in order to offer scalability blockchain capabilities, it is critical to supply robust data management solutions to expedite transaction implementation. Because of its flexibility and versatility, the cloud can provide on-demand computational power for blockchain activities (Dorsala, et al., 2021). In a federation cloud infrastructure, for instance, cloud servers can provide a large-scale range of resources for blockchain platform developers. As a result, the integration of cloud computing with blockchain may accomplish tremendous scaling.

Source: Nguyen & Ding, 2020

IoT sensors are in charge of gathering information from their surroundings and electronically relaying it to adjacent networks such as a ground station, modem, or wireless connection. A blockchain identity is held by an IoT equipment, allowing it to connect the chain of blocks and conduct operations and exchanges with cloud providers. Each resource constrained IoT equipment can, for example, operate as a compact gateway that can engage in the transactional testing procedure via its representation portal. It's possible in blockchain-based sensory deployment scenarios when tiny sensors are linked to the blockchain via the blockchain's portal.

The gateway handles all transactions between sensing devices and blockchain, including establishing transactions, unloading data, and even mining activities. In the meantime, IoT equipment with comparatively big capabilities, such as laptops or strong cellphones, have adequate capacity to service other sleek IoT sensing devices while also maintaining the whole blockchain. IoT equipment may also communicate with one another via IoT gateways in order to accomplish collaborative interaction. In a safe and effective manner, such a blended connectivity approach provides extremely adaptable solutions to IoT adopters. (Nguyen & Ding, 2020)

In the BCoT framework, the Cloud Chain Component acts as a bridge among the IoT infrastructure and business solutions. We focus on a blockchain infrastructure with many servers for a general design, but it also represents the technical aspects of a single-cloud BCoT layout in its entirety. The following are two advantages of this model (Nwachukwu, 2021):

1) utilizing blockchain to provide secure communications network infrastructure and

2) delivering on-demand and dependable virtualized resources for substantial IoT projects.

The blockchain applications and cloud computing capabilities make up the unified cloud ledger stack. Applications powered by the blockchain: In the envisioned design, the major function of blockchain is to enable safe system administration. The blockchain infrastructure is implemented and maintained as a BaaS solution on a cloud platform. To assist IoT solutions, BaaS may provide a variety of blockchain-based solutions (Nguyen & Ding, 2020).

Shared ledger

It denotes the databases that BCoT stakeholders exchange and disseminate. The distributed ledger keeps track of activities like exchanging data and information sharing between IoT equipment and the server. It allows commercial connections in which cloud consumers manage and validate their individual activities while connecting with blockchain clouds.

Consensus

It performs individual activity authentication via consensual processes like as PoW and PoS, which are managed by a community of miners. This operation is critical for BCoT in order to improve blockchain coherence and ensure the system's strong protection. Surprisingly, IoT consumers may utilize their virtualized computing devices to participate in the consensus algorithm and gain incentives for their contributions.

Shared contract

Functionalities can also benefit from BCoT's smart contractual solutions. Smart agreements are extremely useful for building corporate rationale and confidence in the BCoT platform because to their self-executing and autonomous properties. Additionally, smart agreements enable safety solutions on consumer permission authorization or information exchange confirmation once the IoT stakeholder networks conduct interactions, that helps to preserve cloud ledger safety.

Cryptography

This is in charge of delivering publicly crucial encryption to safeguard any information and data sent between IoT and cloud organisations. Digital certificates confirm that all information stored in blockchain is accurate and unaltered, enhancing preservation and safety for individual interactions.

BaaS also provides cloud ledger archiving in conjunction to these offerings. On the virtual machine, decentralised cloud warehouse centered on blockchain may be constructed. Blockchain-based storing maintains IoT information using hash values and use validation on a regular basis to identify any possible information change. IPFS, for instance, is a blockchain-based memory platform that is currently accessible on the cloud, enabling for safe repository across cloud servers. This has also been shown to successfully handle memory storage difficulties caused by centralised cloud architectures, such as data leaking and data administration.

Cloud computing services

Cloud technology, which includes SaaS, IaaS, and PaaS in the BCoT framework, is used to endorse solutions. IoT portal information will be collected by virtual machines and stored in cloud ledger repository. The cloud host also provides intellectual solutions on freed up IoT data by utilising techniques such as data extraction or deep learning. IoT information can be kept in a cloud repository or on-chain in a ledger. Numerous cloud services, on the other side, may be used to enable features like data exchange and cooperative network administration. In this setting, the blockchain element, as an intermediate layer, is critical in regulating and regulating cloud transactions in order to improve cloud business operations to IoT consumers while avoiding cloud disputes.

Many commercial uses can leverage from BCoT incorporation in IoT environments such as patient monitoring, connected cars, sustainable city, energy management systems, and smart economy. BCoT not only delivers helpful solutions to commercial activities such as networking administration and QoS enhancement, but it also ensures confidentiality and protection aspects for applicable areas. For instance, in patient monitoring, BCoT may offer information processing solutions using the cloud's compute capability, assisting healthcare practitioners in proactively evaluating patient statistics for improved medical treatment. In the meanwhile, blockchain ensures patient care system protection by providing transparency and authentication capabilities throughout health data transmission and analysis. (Nguyen & Ding, 2020)

Blockchain technology is being used to create an Internet - of - things intelligent metropolis design that consists of three basic layers: intelligent blocks, a peer-to-peer system, and the cloud. Due to the inefficiency of public ledger for a high amount of networking terminals, such as IoT equipment in intelligent cities, the suggested system recommends a sleek blockchain with minimal computational and material needs. All contacts among IoT equipment, cloud warehousing, and peer-to-peer terminals are labelled as activities, which are documented and safely kept on ledger in an encrypt way. A blockchain-based architecture is also being investigated to offer safe intelligent contracts applications for intelligent cities' collaborative consumption. IoT device media content is delegated and kept secure as irreversible ledgers in decentralized IPFS-based cloud storage.

House technology, in the perspective of intelligent cities, provides structure to a connected home, which is the predominant function of a city of the future. An intelligent house is a system of Internet of Things (IoT) devices outfitted with autonomous gadgets, sensing systems, and monitors that gather data from the surroundings and send it to a specific node, such as a workstation or a cloud server, for processing. Safety, dangers, assaults, and privacy protection remain unresolved challenges with smart home automation. A blockchain-powered BCoT with decentralized, safe, and confidential characteristics would be a potential answer to these safety concerns (Nguyen & Ding, 2020). Blockchain technology is utilized to create a decentralized data security structure that ensures the overall system's excellent durability and dependability without the need for third-party assessors.

Health care system is a sector of the economy in which businesses and healthcare centers offer health care solutions, hospital instruments, and healthcare coverage to enable individuals to get treatment. Implementation of BCoT concepts has the ability to overcome important concerns in respect of safety and operational effectiveness, allowing hospital facilities to develop and present medical centers to be transformed. The incorporation of BCoT in hospital intends to bring latest electronic solutions such as improved healthcare information exchange, health information preservation, and protected systems administration.

Considering the fast advancement of current sensors and actuators, communication, and intelligent systems, past few years have seen enormous expansion in ITS, which has substantial influence on numerous parts of our life with intelligent transportation infrastructures and cars, as well as improved transportation operations. Smart mobility is a critical IoT technology that pertains to the combined structures of information systems and vehicle operations in mobility infrastructure. The safety vulnerabilities posed by dynamic V2V interaction in untrustworthy vehicle contexts, as well as dependence on centralized network authority, are a key challenge in connected vehicles. Blockchain has the capability to contribute to the creation of a safe, trustworthy, and decentralized ITS environment (Vladyko, et al., 2022). The integration of cloud technology, which has infinite data governance abilities, and blockchain, which has excellent safety characteristics, has the potential to improve quality and reliability.

The implementation of BCoT in schooling is currently in its initial phases. Only a few academic organizations have begun to employ BCoT technologies. The majority of existing systems employ BCoT for the aim of authenticating and safely transmitting scholastic diplomas and private details of individuals, as well as academic organizations' training databases. Intrinsic blockchain ledgers and cloud - based services may be used to create safe and trustworthy learning ecosystems that encourage scholastic cooperation.

To serve consumers and businesses, cloud technology provides a wide variety of outsourced activities, comprising memory and calculation. Generally, freelancing companies incorporate online banking and confidentiality concerns. Nevertheless, many conventional business offerings must depend on an authorized intermediary to ensure impartiality and settlement completion. As a result, ensuring safe and equitable payment of outsourced activities is critical for cloud-based systems. Because of its verifiable and irreversible characteristics, blockchain has surfaced as a good contender for resolving cloud platform privacy challenges and simplifying cloud platform administration. The contributions present a ledger equitable money transfer framework for distributed hosting outsourced activities. By utilizing a resource administration system powered by blockchain, the suggested solution assures coherence and substantial honesty characteristics (Nguyen & Ding, 2020). Equitable settlement may be made between cloud customers and outsourced solution companies via payments that are maintained and confirmed by blockchain without the intervention of an outside entity.

Blockchain has evolved as an empowering innovation for driving intelligent enterprises, supported by its decentralized P2P communication network, and the confluence of CoT with blockchain as a BCoT concept promising to strengthen business environments with greater protection and improved commercial system performance (Nguyen & Ding, 2020). There is a substantial amount of scholarly activity in the integration of BCoT in intelligent enterprise, which may be divided into three categories: smart industrial production, energy management systems, and intelligent supply - chain management.

Blockchain is utilized in data and resource collaboration activities in connected vehicle administration to provide maximum security standards such as identity verification through agreements and privacy protection through encryption. An unanimity technique in the blockchain infrastructure encrypts and appends the vehicle data to the chains throughout the data and resource transactions. Furthermore, blockchain may be used to build a secured community infrastructure that allows for smooth interaction across omnipresent automobiles for resource administration, value sharing, and cooperative confidence. The research offers a system of cooperation across several automobile platforms, with blockchain used to construct a coordinating method. Vehicles from several automakers may be interconnected efficiently using their own cloud, which is dependent on a decentralized method that provides system administration, resource distribution, and cooperative confidence inside the V2V transmission infrastructure. Blockchain technology is being used to enable peer-to-peer communication across various clouds of automobiles while maintaining strong protection standards.

Source: Nguyen & Ding, 2020

They suggest a strategy that uses blockchain-enabled vehicle mist computation to provide excellent safety and confidentiality for the application. Driving information, in specific, is captured and encoded on a remote server, while its hash function is saved on a digital ledger, allowing information transparency and dependability. The BCoT paradigm is used in this study to provide a job management system for a vehicle virtualized ecosystem. The establishment of an automated vehicle cloud (AVC) environment in which nonrepudiation of implementation among activity communicators and assignment executors (automobiles) is assured by secure and transparent administration on blockchain. Meantime, the research proposes a perfectly alright conveyance simulation for insurance companies facilitated by blockchain and Cloud of Things (Zyskind, et al., 2015).

The technology is divided into two sections: an Internet - of - things information collecting and analysis method for vehicle behavior statistics and a cooperative blockchain ecosystem comprising Ethereum network for vehicle function administration.

Source: Li, et al., 2021

Vehicle Perimeter Computational boosts the computational capabilities of conventional VANETs, but also introduces a slew of additional issues, most notably major protection, and trustworthiness concerns. Yang et al. presented a widespread and decentralized trust evaluation paradigm for automotive systems centered on the blockchain approach, as seen in Figure. Automobiles validated the information they got from respective neighbors by using the Bayesian Interpretation Framework. RSUs were in charge of assessing the message's trustworthiness to the associated cars in the developed framework. They put the trusted information into blocks and proceeded to add it to the trustworthy chains. To assist RSUs in reaching agreement, the study proposed a novel prediction technique based on combined Evidence and Confirmation. The concept took into account two types of threat references: assaults from malevolent automobiles such as communication impersonating, verbally attacking, and poll stacking attempts, and cyberattacks from hacked RSUs (Li, et al., 2021).

Source: Zyskind, et al., 2015

Figure illustrates the desired process situation using an easy-to-understand illustration. In this application instance, three different sorts of responsibilities are implicated: automobile operators, transport carriers, and insurance firms. The interplay and relationship among these three functions inspires the organizational strategy described in this research. Several of the realities presently is that carriers frequently use GPS or other IoT equipment on-board to govern the fleet or analyze highway conditions. As a result, carriers may gain valuable information from real-time mobility Sensor information. Transport drivers are also regarded "independent entities," therefore they are believed to be sincere, i.e., they adhere to the procedure and regulations as outlined in prior research. To fulfil the fine-grained insurance scheme, a few crucial characteristics such as IoT information gathering, travel database management to create protection requisite measurements, and the insurance pertaining journey summarized documentation, independent review stipulation, autopay means of exchange for security and impartiality are regarded to be communally realized for a collaborating transportation networks, in which Internet and blockchain innovations fairly fit these implementation characteristics for an incorporated remedy (Xiao, et al., 2020).

Source: Xiao, et al., 2020

In line with the business situation, we develop an Internet - of - things and distributed ledgers cyber infrastructure, as shown in figure. In order to assist our conversation, a standard is defined in figure, as follows: the connection (communication link or application execution) is labelled in Arab numbers, and the major operational elements or systems are specified by Roman numbers. In the next talk, we'll commence with main components (Xiao, et al., 2020).

(i) GIS is a processing and archiving infrastructure that allows for the analysis of large Metadata from the car's sensing devices. A GIS processor is installed at the vehicle driver's location to produce travel insights and coverage subscription fee information. The computing capabilities used within the GIS processor are referred to as off-chain offerings. 

(ii) The goal of Hyperledger Fabric is to create a cooperative connection among health coverage firms and transport providers that is primarily responsible for collecting automobile journey data for insurance decisions in a tamper-proof manner and enabling auditing purposes. Furthermore, once the car's on-board Internet - of - things information is collected, the block-based applications established using the HF chain act as the controllers of off-chain GIS applications to computerize the GIS statistics. Because such legitimate journey statistics gathering happens at the conclusion of each journey per car, and therefore a significant volume of journey operations is predicted throughout peak times, the selection of permissioned ledger to record travel statistics takes efficiency into account. Distributed ledgers are susceptible of managing far more operations with higher efficiency than blockchain networks, making them appropriate for these immediate solutions.

(iii) The general network component of the Ethereum system in our approach intends to calculate the insurance costs depending on the journey parameters stored in the HF ledger, in order to issue policy certificates and fulfil the payments’ function. These services may be arranged on a regular basis, thus there is no strict punctuality need. Furthermore, Ethereum has a wide common base of users, and the established token transaction credited with the vehicle's certificate, and premiums could be simply controlled by the Ethereum networks for the automatic payment function.

The following is an explanation of the links among various elements: First, IoT sensing information are submitted to the GIS motor at the final moment of each vehicular journey ride for journey statistics computation, as shown in figure as number one; then, the journey measurements are forwarded to HF blockchain for incorruptible documentation, as shown in figure number two; and the journey measurements are preemptively enquired by the Ethereum smart agreement on an everyday grounds to generate the certificate and high price expense, as shown in figure. Figure shows the public blockchain HF chain infrastructure and the Ethereum infrastructure. As previously stated, administrators and premiums firms must supply client terminals that engage in both the Hyperledger and Ether systems, whilst motorists must simply engage in the Ether system with a payment account for disbursement. It should be highlighted that the cyber infrastructure may be used by various providers, insurance providers, and a vast number of driving subscribers (Li, et al., 2021).

The link in the image demonstrates an extended approach for the untrustworthy operator’s paradigm; in this scenario, insurance firms must additionally operate a GIS processor node that is possibly supported by the blockchain network or other safe off-chaining technology. The primary risk under this paradigm is one of security since transport companies or individuals frequently do not want some other entity to have exposure to all of the elevated digital copies. Possible solutions include relocating some GIS assistance to regularized Ethereum smart contracts so that they can be handled across unanimous agreement, or, more effectively, having adopted the private information off-chaining method to be realized in line with smart contract verification, such as proof-of-execution under the zero-knowledge proof (ZKP) arrangement.

In our approach, the computational flow following the IoT data transmission comprises an engagement seen between off-chain GIS processor and the HF network, as previously mentioned. There are various crucial and pragmatic aspects to integrate into such on-chain and off-chain connectivity architecture. As already stated, the function of drivers is believed to be authentic or semi-authentic. This strategy is widely accepted since, as independent bodies, operations are fundamentally unmotivated to help insurance firms or motorists in committing possible insurance scams. In reality, providers such as mobility officials are ready to encourage proper driving behavior and provide healthy mobility in order to fulfil their obligations, and so, GIS computation jobs housed by providers may be through of some confidence (Xiao, et al., 2020).

Source: Xiao, et al., 2020

Moreover, in practice, mobility providers might refuse to provide mobility information owing to privacy protection considerations, therefore GIS data must still be managed by its stakeholders. There are even more obvious grounds for believing about on-chain versus off-chain architecture from a technical standpoint. In terms of memory, as we all understand, Geolocation information is very large and accumulates over time; hence, putting all mobility information on chain is not feasible since chain demands replicated memory at every node. As a result, contemplate off-chaining these large amounts of Geographic information that are supplied at the conclusion of each journey. The actual Geographical information's information, including the verification and meta explanation, is likewise saved on-chain, with tiny footprints (Eberhardt & Tai, 2018).

Data integrity is ensured by comparing and verifying information from both the HF and the GIS engines. Traffic GIS data analytical solutions are typical computationally intensive jobs from the standpoint of computation expense. Putting time-consuming GIS computational activities on the chain is not a good idea (Xiao, et al., 2020). Via the HF network as an instance, any completed tasks must be confirmed by peers using the agreement method, and the identical replicated calculations must be conducted at each node for approval. Such computationally repeats for large analytical activities are a wastage of computer energy, hence placing GIS analytical activities on the chain is not recommended.

Considering on the foregoing factors, researchers devise an approach for smoothly integrating the HF ledger "on-chain" and "off-chain" applications. The fundamental concept is to use an HF ledger consensus protocol as the implementation controller for "off-chain" GIS analytical solutions (Eberhardt & Tai, 2018). Figure depicts the features of the connectivity architecture. The fundamental flow is as regards: First, as shown by number one, at the completion for every travelling cycle, the actual journey sensory information is sent to the GIS motor servers for journey information preservation, while a distinct journey referencing identification is produced with car identification and transmit information. The journey documentation transaction is subsequently documented at the HF ledger, with the journey referencing identification and other journey details entered as described in procedure number two, which is submitted for future handling and auditing purposes.

The consensus mechanism then successfully triggers the GIS computation services implementation for travel statistics done at the GIS motor servers, as stated by number three. To complete the procedure, the GIS server’s terminus and application registered metadata are encoded in a shared ledger, where the GIS engines terminus connects to the engine's Address and the matching GIS analytical capabilities are specified. Following the fulfillment of the journey GIS analysis activities, the journey aggregate findings, comprising the travelling length and vehicle behaviors, are uploaded as a transaction to the blockchain database for durability, as shown in figure.

As a result, the important functionality occurrences and premiums data are recorded on a blockchain database, whilst the entire process flow and reasoning are mechanized by the established shared ledger, resulting in efficient combination of "on-chain" and "off-chain" operations. It is important to remember that the chain in the graphic solely relates to the HF chain infrastructure. The Ethereum-based community blockchain infrastructure is only in charge of premium subscription fee operations. These solutions specifically involve insurance plan service charge computation centered on the journey overview obtained from the HF ledgers, standings and certificate creation providers relating to the car's journey and travelling behavior, as well as compensation associated details, whereas the reward methodology could also be realized premised on the Ethereum platform (Xiao, et al., 2020).

With all the journey IoT information supplied from the cars, the GIS activities run at the GIS machine comprise a sequence of "off-chain" calculations to create the perspectives, also including driving behavior, necessary for insurance price computation. The basic need of journey GIS statistics is to use a set of important journey measurements to accurately reflect the facts about what transpired during a journey drive. To ensure the accuracy of the investigation, the operational flow of the GIS analyzing solutions is tightly standardized in terms of data integrity checking, map alignment, and so on. Because unexpected errors in journey data processing owing to detecting performance degradation or data loss may contribute to data integrity issues, unprocessed GIS data must be treated for accuracy.

Source: Xiao, et al., 2020

Outlier elimination to remove the anomalous entries and information structure with a regular sample rate to permit subsequent restoration of the journey itinerary are examples of common quality improvement procedures. Trip itinerary creation is a vital operation that affects the reliability of journey metrics such as duration and acceleration trend computation. The location-matching technique should be used to ensure that the car's path is matched with vehicular roadways and to improve the correctness of the journey itinerary depiction (Xiao, et al., 2020). The remainder of the computer procedures are associated with the development of a journey data overview, a journey analysis such as a velocity range, and other specialized journey assessments defined for insurance applications using the reconstituted journey itinerary.

GIS systems ultimately convert the actual travel information from the car into a list of statistical metrics about the journeys. At that point, the travel reports are transmitted as activities to the permissioned HF ledger for permanence. In terms of load balancing and cybersecurity robustness, antiquated information may be preserved to be linked with the insurance scheme. For example, if automobile insurance price is weekly, then just the most recent one week's information has to be downloaded on a regular basis, while prior information can be kept. As a result, even if information accumulates in the database, query speed is unaffected and may remain expandable.

Seguros Equinoccial collaborated with IBM Global Technical Solutions and a regional corporate collaborator to create an IoT workaround that incorporates GPS. The software collects and analyses information using IBM Cloud Watson Campaign Automation, allowing individuals to engage with their automobile to understand about personal commuting behaviours. It also contains features that encourage safe driving habits. The software captures every time a motorist speeds fast, decelerates rapidly, takes a sharp curve, or performs any other activity. The information gleaned from the acquired data is then utilised to develop information regarding driving behaviour. This information is then collated for statisticians, who use it to determine more precise costing and evaluate motorists based on their motoring abilities and tendencies (Griesbach, et al., 2018).

The program's goal is not to penalise drivers, but rather to encourage them to change their driving behaviours. If the score is poor, there is no payment spike; if the score is strong, there are only perks and discounts. The score was created as a trial project at the finish of 2017, when Seguros Equinoccial deployed the technology in 500 active client vehicles, distributed the application, and started assessing eight distinct criteria. Consumers now obtain a push message regarding their performance once they've done motoring via the Connected Car mobile app, along with tips for how to improve. It also sends out service notifications. When motorists manage to recover their performance ratings, they receive virtual currency that may be traded for items, activities, or even a percentage-based refund on existing insurance premiums.

Blockchains appear to have a wide range of applications, particularly in domains where third parties have traditionally been used to create trustworthiness. The blockchain, according to Atzori (2015), could reconstruct culture and government as a whole. If individuals began to organise and safeguard civilization through decentralised networks, many activities may become redundant. "Delegation of authority of federal programs using public blockchains digital assets is conceivable and necessary, because it may considerably boost good governance performance," he adds. In impoverished nations, reorganising society is critical. Using the block chain technology, capital can be better safeguarded. Property owners, particularly in the developing countries, face difficulties proving possession when the regional government, for instance, seeks to confiscate the populace. By incorporating property rights into the block chain technology, these serious dangers may be managed. Nevertheless, as Glaser (2017) points out, the bridge among the online and actual worlds might be a missing piece in a blockchain platform's digital trustworthiness.

Scientists and authorities are also debating whether blockchain-based crypto-currencies could perform the tasks of actual currency (Directorate of Intelligence , 2021). Mishkin (2010) defines currency as "something commonly acknowledged in exchange for products or commodities or in the settlement of liabilities." Cryptocurrencies, according to Luther & White (2014), are only utilised as a means of trade infrequently nowadays.

According to Glaser et al. (2014), Bitcoin is mostly employed as a liquid investment. However, creative techniques by businesspeople, who are building crypto-currencies as a replacement for fiat currencies, may make purchasing and recognizing crypto-currencies simpler. When purchasing a property, homebuyers are faced with high transactional charges. "Block chain technology may lower ownership premiums and deductibles and provide $2–$4 billion in potential savings united states by decreasing mistakes and human work," according to Nofer, et al. (2017).

While engineers and scientists are primarily interested in the technological and cryptographic problems in this domain, scientists in the discipline of Management and Technology Information Management might concentrate on customer strategy, trustworthiness and confidentiality issues, and the acceptance or non adoption of novel technologies. Furthermore, disrupting technology has the potential to destabilize numerous current enterprise strategies, as well as develop fresh ones, and have far-reaching consequences for whole sectors. As a result, research focusing on the convergence of technologies, economics, and value propositions is extremely beneficial (Nofer, et al., 2017).

The system of vehicle insurance and trust management requires a lot of dynamics to be involved within in order to keep the system operational. There are mainly these 10 requirements for the system to run:

(i) Internet Connection

An internet is something which allows the communication between the different vehicles and systems. So, a car should be connected with networks and the vehicle must have the RSUs in the connecting range to transfer the data over internet. Whatever the data is being collected from IoT side of the vehicle, will be send over RSUs. The RSUs transmit the data to a fog edge computing and then cloud computing platform. The cloud computing platform itself can be connected to a blockchain and work on a blockchain network. Nevertheless, internet connection allows this whole network to reciprocate signals and stay in a loop of the complex system.

(ii) GPS Data

The Internet of Things comprises of sensors to collect the data. Now in order for the insurance provider or vehicle safety department to get the data of the car which can be used for insurance and trust management, the cars must have sensing unit which senses the position of the car and provide the coordinates to the servers in order to analyze the data for the purpose.

(iii) Speed Data

The speed of the vehicle is measured through the speedometer sensor and this information can be useful for the insurance and trust management purpose because the speed and risk are interconnected in terms of driving safety. The meaningful insights from GPS can be made in real-time if the speed of the vehicle is provided. Therefore, the speed sensors are also the requirement as a part of internet of things side requirement for the application.

(iv) Other Sensory Data

Some other sensors in the vehicle which can provide more insights of the real-time vehicle can be an aid for the application. Those sensors include the sensors to know how many passengers are in the car, if the passengers are wearing a seatbelt or not, what is the driving pattern of the car, is the lights on or not, etc. The more the sensors, the more complex system will be. However, if the system is perfectly aligned in order to perform the application objective, the management and use case scenario of the sensory information utilization is required.

(v) GIS In-cloud Computing Unit

The processing of the position data of the vehicle is the primary requirement in order to provide the insurance and trust management service for the vehicles. In-car processing would take a lot more hardware and software requirements for cars and therefore, it is better if the data is sent to cloud and the cloud computing unit is used to process and analyze the real-time data.

(vi) GIS In-cloud Storage Unit

The cloud processed data needs a storage unit to temporary store the data for the processing result storage purposes. The data can then be sent over blockchain for higher protection. As there is seamless integration available between cloud and blockchain, the in-cloud storage unit is the best way to keep the track and record of the data to analyze or use in the future analysis if needed.

(vii) Ethereum Blockchain Network

So, the trip metrics analysed in the cloud computational unit can then be sent to the distributed ledger of blockchain. Every transaction made with the vehicle will be updated in the blockchain platform of Ether so that it can be protected and used with the access key whenever needed by the computational unit, insurance firm, or vehicle management corporation.

(viii) Hyperledger

Hyperledger is a worldwide corporate ledger initiative that provides the structure, rules, principles, and resources needed to create fully accessible blockchain network and possible applications for a variety of sectors. Hyperledger's initiatives provide a number of corporation public blockchain distributed ledger systems, in which networks members are familiar with one another and so have a vested stake in the general agreement mechanism. Therefore, this is required for safety and security of the vehicle data.

(ix) Multimedia Devices

Multimedia devices are not very essential in this application. However, in order to get a real-time update about malicious car nearby or any other trust feature, multimedia can be utilised as a feedback system. Moreover, it can also be used for other purposes such as the insurance premium tracking or providing feedback about the driving conditions, etc.

(x) RSUs

A Roadside Units are a Dedicated short - range transmitter that is installed across its edge of a roadway or public walkway. An RSU can be placed on an automobile or handled by person, but it can only function while the car or hand-held unit is immobile. Additionally, an RSU functioning under this portion is limited to the area in which it has been granted a licence to function.   In its connectivity region, an RSU transmits or trades information with Base stations. When necessary, an RSU also gives channel allocations and operational directions to Base stations in its operations region.

Use-case diagrams depict and clarify the context and needs of a complete system or its key components. A simple use-case diagram can be used to model a complicated system. Use-case diagrams are usually created in the early stages of a project and referred to throughout the developmental stage. Below is the use case diagram for the application case of car insurance and trust management using cloud and blockchain.

Source: Made by Author

The above use case diagram for the safety and insurance management for cars shows that the network of these systems is all interconnected for a purpose. The use case scenario here is developed in a way to simply represent the system and therefore, it is used only two drivers, two cars, an inspector, safety department, a vehicle department, and two insurance firms. However, in real-world case, the quantity of these entities are enormous.

All vehicles are connected to all the elements:

If we talk about driver 1 first, his car is connected to the inspector, vehicle department, insurance firm n, and a safety department. So first, inspector is connected in the network because in case of any abnormality or doubt, the inspectors have authority to the blockchain consensus in order to check the vehicle information and take actions if there is something susceptible to cause risk is detected.

The driver 1 car is also connected to the vehicle department to update them if the changes in the current situation of the car is detected. The vehicle department is generally analyzing the maintenance condition of the car from the car usage statistics and therefore, the sensor data of the car journey length and duration will be updated to the cloud ledger and can be accessed by the vehicle department for use. That department can notify the driver if there is any kind of maintenance for the car is required.

As there are multiple insurance companies in the market, a vehicle is only connected to any one insurance firm to update the usage statistics and driving journey statistics to the insurance company including the journey start to end details and the timeframe. The insurance firms use this information to calculate the user specific premium bill as per the car usage. In case of any offense is detection, the insurance companies charge the driver more.

The driver 1 car is also connected with the safety department because the safety department monitors the coordinates of the car in comparison to other cars. If the department detects any safety concerns, they can let the driver know or send the immediate support.

The same with driver 2. The driver two is connected with the insurance company 1 here. The thing is that those two cars are not connected to each other, but the relative trust management can be performed as those cars are connected with the same safety departments.

Inspector works as a bridge from vehicle department to drivers:

The inspector is only connected with the vehicle department and all the vehicles. The inspector has access to the ledger of any cars so that he can access the user specific information if any abnormality is reported from the vehicle department.

Vehicle Department acts when abnormality detected:

The vehicle department is connected to almost all the elements because it is their responsibility to take the reports from every element and analyze it or store it for any kind of safety of insurance application.

Insurance Companies monitors usage and reports:

The insurance companies are connected with the vehicle department, safety department, and the cars to calculate the risk factor and the car usage statistics to provide the optimal premium charges possible for the drivers.

Safety Department updates the accidents info:

The safety department here is connected to insurance companies and drivers only to collect the incidences information if any incidents happen and update the insurance companies about it so that the insurance company can revise the premium plan and make it a little higher after the incident.

Source: Made by Author

In the discipline of system engineering, a sequence diagram depicts attribute interactions in temporal order. It represents the types of scenarios components and the flow of information transmitted between them in order to conduct out the scenario's operation. In the rational view of the systems under creation, sequence diagrams are generally related with use case realisations.

This sequence diagram shows the sequence of process for the three important scenarios for the insurance and trust management model:

(i.) Updating the changes in vehicle position, time, location, speed, and passenger to safety and insurance department:

· The IoT devices in cars connected to clouds are updating these changes to safety and insurance department.

· The safety and insurance departments use cloud platform and the on-cloud GIS information updates to analyze and record the information.

(ii.) Safety and Insurance department updating the blockchain information in new ledger for the particular vehicle(s).

· The safety and insurance department have public keys to access the information of any car records in order to process any cases.

· The data received by safety and insurance department are updated on a blockchain distributed ledger.

(iii.) The car intelligence system directly communicates with the surrounding cars and inform the driver if there is any malicious car around using their public key access to their records.

· The cars have direct cloud blockchain access using public keys.

· The cars do not communicate with each other directly but acts in a way they are communicating with each other to increase the security and safety.

· The public keys are the elements that allows the cars to detect if the car nearby is honest or malicious.

· The car multimedia system informs driver if it is a malicious car.

· The trust values are updated to the safety & insurance department and cloud ledger in case an accident happens.

Source: Made by Author

The flow from one action to the next is represented by an activity diagram, which is essentially a flowchart. An operation of the system might be used to characterise the activity. From one operation to the next, the control flow is drawn. This flow might be sequential, branching, or in progress at the same time. The activity diagram made as above shows how the changes in the car systems are going to be detected for insurance and trust management application.

a) The first change is going to be detected when the car starts. As soon as the power is on, the change gets detected.

b) After starting the car, there are three changes that the car is going to measure. The IoT systems on the car will detect the speed of the car, location of the car, and will ask for the number of passengers in the car to update.

c) The speed, location, and passenger information is going to be updated in the car database but will not be updated to the cloud yet.

d) The system will monitor if the speed changes, location changes, or the passenger information changes.

e) If there is a change, the database will be created and will be sent to the cloud blockchain server for further operations.

f) The new updated information sent on cloud is going to be validated first and then stored in the cloud blockchain network.

g) Once the results are updated in the ledger, the insurance and trust management company also analyze if the driver’s policy is eligible or not.

This whole activity diagram shows how the IoT in car is going to make decisions about the changes and update the changes to the blockchain cloud ledger. The dotted line in the middle indicates that the information is sent outside just the vehicle IoT system. This is very important diagram because in case of blockchain cloud, we are going to record just the changes happened to the existing information with timestamp to save the time, efforts, memory, and processing.

4.5 Quantitative Variables for Vehicle Hazard Score System

For the simulation of the trust score and insurance, a common factor as a hazard score system is designed for the system simulation understanding. The table below provides the variables and its quantifications for the simulation purpose. In order to understand the behaviour of the examined system, this quantification can be useful for the simulation of the model after casual loop and stock and flow modelling.

Table 1 Quantitative Variables for Vehicle Hazard Score System

Source: Made by the Author

The hazard score is calculated based on the severity of any accident and it is measured out of 100 for quantification. The accident prevention possibilities and the resilience of the multimedia communication system is measure out of the fraction of one.

In the next section page, the casual loop diagram is made by the author for this system. The diagram was developed using the Vensim tool. When the actual hazardousness is higher than the targeted ones, the resources for accident prevention gets allocated more which B1 loop is representing. The B loops’ intensification can lower that gap between actual hazardousness and targeted hazardousness.

The same way, the loop R1 shows that as the more safety resources are given in the system, the more the risk rate is, the communication channel also helps to report the hazards so that the prevention can be done. The more the risk is there, the more hazard score will rise in the blockchain and cloud-based vehicle insurance and trust manamentnt.

4.6 Casual Loop Diagram

Figure 17 Casual Loop Diagram

Source: Prepared by the author

4.7 Stock and Flow Model

Figure 18 The Stock and Flow Model

Source: Made by the Author

Risk = -

Safety Culture =

The safety performance and culture flow diagram is shown in Figure 18. Hazard score status is a level variable, whereas risk and safety culture are rate factors that influence accident status. The rate of accidents is proportional to the risk, and a higher risk equals a higher rate of accident severity. Safety culture, on the other hand, lowers the accident rate. Risk and safety culture are affected by other factors.

These are the relationships found from the dynamics:

Hazard Score = Risk – Safety Culture

Risk = 1/Hazardous Drivers Rectified

Safety Culture = Safety Focus x Resources Allocation

The vehicle insurance and trust management system design is proposed in this dissertation based on the analysis of the requirements. The whole system description was not possible to make and therefore, the research has focused on analyzing the system by forming use case diagram, sequence diagram, and activity diagram. These three diagrams essentially include all the important factors for the system and can be researched and developed further using other methods in the future. The diagrams are made in an easy-to-understand format and includes all the required factors for this paper. The model can be more complex if more sensors and requirements in the operations added. However, in order to make it work for vehicle insurance and trust management system merely, it fulfils the purpose. This blockchain and cloud based IoT application can be practically possible as per the system design interpretation from this paper. There are some aspects of the system dynamics which are not involved to reduce complexity:

a) The diagrams does not have all the elements there should be in order to entail the essential parts clearly with simplicity.

b) Some elements are not included in the analysis because of the limited focus of the dissertation. The whole dynamics analysis is not possible to demonstrate using a diagram on page.

c) There may be inconsistencies between the models. These ideas and diagrams are developed using author’s best knowledge and may contradict in the future as the ideas grow over time and evolve.

This thesis does not focus on implementing the vehicle insurance and trust management model within the research. There are certain aspects which should be taken care of when the implementation of the model is to be carried out using this dissertation:

a) The model includes many elements and there might need more than just used elements in the model. Therefore, for implementation, a few changes in the model or a few additions are required.

b) The implementation should at least consider the basic requirements mentioned in the practical part.

c) The author advises using a simple system to avoid cost and shorten the complete structure. The number of cars and insurance companies are going to be so many in terms of quantity. That is why the implementation would cost a lot more than it seems from the model. The practical implementation of the model also will require high level of understanding of IoT, cloud, and blockchain in real life.

d) This system is fully interconnected within. All the components are connected to each other and depends upon each other in order to operate. Any failure in the system can fail the whole system. Therefore, while implementation, it should be taken care that all the components are functional in terms of hardware and software both.

e) It is also recommended from the author that the internet connection and the availability of RTUs should be made sure to keep the car connected with the cloud and blockchain. Any connection loss can result in the total failure of the system. This operation of the system can be automated as well.

f) It is also recommended to test the system once it is complete. Because of the complexity of the system, the problem is certain to arise, but the model can be adapted with the problem solutions every time to get a better model using trial and error method.

g) The GIS processing on-cloud is an important thing, but the coordinates should be made sure that they are accurate so that any harmful consequences can avoided.

h) Some of the advanced techniques can also be implemented such as artificial intelligence, deep learning, and other automated techniques to advance the application workarounds. However, in that case, the system diagrams will require to be redesigned to adopt those elements.

The purpose of the dissertation was to integrate cloud computing and blockchain to make an IoT application of vehicle insurance and trust management possible with high reliability and security. The dissertation is based on a review of the research done on the core issue and the formulation of a collection of analytical observations, simulations, and modelling. The study of literature has largely focused on two parts: blockchain technology in cloud computing and how it is being used with IoT, as well as the integration and applications of IoT in blockchain based cloud computing and the system dynamics to be utilised for the analysis. The system dynamics are analyzed in the practical part with all the basic requirements and the diagrams were developed. The dissertation successfully develops the system dynamics diagrams and provides deliberate recommendations for implementation.

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