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Web Intelligence Based Flexi Vehicle Insurance Application

Computerization is currently a key element in everybody’s life – individuals, businesses, travel sectors, medical services and many more. As the world is pushing ahead, the web and innovation have been the implications that these areas use to contact individuals and get benefit from the brand or administration they advance. The private protection area is perceived as one of the quickest developing ventures. This quick development has powered unfathomable changes over the previous decade. These days, most valuable resource protective items exist, such as homes, vehicles, gems, life, etc. All insurance agencies are at the forefront in taking leading tasks, measures and numerical models in order to increase benefits by adapting customer claims. Customary techniques based only on human-in-the-loop models are extremely tedious and incorrect. In this paper we are establishing a safe and computerised protection framework that reduces human communication, ensures safeguards, alerts and illuminates hazardous customers, distinguishes misleading cases and reduces money-related unhappiness. The proposed Framework for Vehicle Protection Strategies is a single-page online application that aims to establish an entirely practical, free framework to monitor vehicle insurance records. It is designed to provide such insurance agencies with an online stage for exact preparation, coordinated information, production recovery and record capacity.


1.
Introduction For car manufacturers, it is becoming increasingly important to promote responsive and competent responses to the safety and well-being of vehicles. In fact, vehicle safety is important to reduce vehicle crashes and their effects on passengers from injuries and deaths while being hit or crashed. In addition, such interest was distributed by insurance agencies. Because the defense business relies on risky movements, the support system recognizes the challenges of later defenders. Again and again, guaranteed payments are financial. The defense industry faces a number of challenges. Improper cases are one of the most common problems affecting various classes of defense and influencing the intelligence function of a group of insurance companies [1]. The Association of Certified Fraud Examiners (ACFE), the main enemy of an outsourced organization and a major provider of faulty preparation programs, sees fraud as an indication of cunning and mistakes by a person or object that can lead to some unfair advantages for one person or another. Security robberies have had serious repercussions for several years in the security company. It is considered the second-largest case in the U.S. and costs more than USD 80 billion annually, according to the Federal Bureau of Inquiry (FBI) . The visual strategies for cultural protection are complex and tedious. They depend heavily on the king's trials, on the officials, and on the administration of special tests. Physical recognition of fraudulent cases involves additional costs and errors. Late detection of improper representation can also lead to further harm to insurance companies. 21% of serious injuries and 18% of all personal injury claims at full discount were found to be misleading. [3]. There is therefore a need for pressure to develop quick and productive responses to fraudulent cases. Because of the complexity of misleading laws under conflict protection, these organizations, which can reduce their level of competition and influence their business ideas, add a significant amount to their separate plans to cover the costs of those malware claims. An example of a robbery study and a prediction of the cost of accident detection is proposed in [4]. In this work, practical technology was used to calculate the different rates and to anticipate questionable cases of mining information. Three separate dividers were used to predict misleading cases and premium rates. Statistics J48, Naive Bayes and Random Woods were selected for order. The research presented in [5] used common sense to define fluffy values to improve identification of robbery. The latter method has been used to anticipate negative representation by using the various participatory capabilities of large and high-density data sets. A separate robbery in collision protection was explored in [6] where based on distance, spatial techniques and insights were used to detect incorrectly defined events. Accuracy measurements and F measurements were used to test the proposed model. In any case, this strategy is not suitable for large databases and unequal data. Vehicle safety can be a major topic for inspections of the automotive sector and collision prevention organizations. It is very important for them not to pay for damaged vehicles and to face too many charges. In fact, counterfeit cases pose a serious and costly problem to insurance agencies and end up costing them more than a billion dollars a year [7]. Fakes also have inexpensive consequences for the public as their costs are borne by the road owner by increasing their cost to cover the provider unfortunately. In addition to easing fraud schemes, some insurance companies are investigating innovation arrangements not only to improve customer safety and driving experience, as they are often fraudulent, tedious and often lead to erroneous results. In this paper, the proposed Vehicle Safety Strategy Framework is an online one-page program designed to create a usable and fully-fledged free-of-the-art vehicle insurance company records record. It is built with the expectation of providing insurance agencies with an online component for accurate preparation, information coordination, and productive acquisitions and records [8][9][10][11][12].

2.
Related works The block chain has attracted a lot of interest in experimentation as it is a new concept that can help solve problems in many areas [13]. The naming of Block chains is certainly not only related to the background and bank applications in this section. These innovations can be used in a variety of fields, but not limited to: data security, medical services, networking and integration. In the area of network protection, the block chain is used as a means of minimizing DDoS attacks as shown in [14]. The final test reveals a strategy to reduce DDoS attacks by creating a private network that uses CDNs with members who believe they have been authorized by military or government offices. In the area of medical care, blockchain-based structures, Internet of Things and new objects in AI [15] used to block, transmit, disconnect and store data on IoT gadgets connected to a block chain network. In addition to facilitating access to various partners, the blockchain framework was not only used to store and store patient information. In the defense sector, few studies have examined the use of block chain to ensure simplicity and roboticism [16], [17]. Block networks ensure the respect and acceptance of social security information records of social insurance organizations. In fact, it is used for a range of social data, individual access to social information, and access control strategies. In [18], a framework mixed with health services is recommended for the collection of information on individual well-being and sharing to support a concerted effort between individuals, health care providers and medical camps.  [19], which uses a consensus agreement with sensory information as a model protection model, gradually changes the installation of vehicles / weather sensors in a timely sensor to help reduce the cost of strategic change and protection of breath and respiratory protection. Other investigations have devised a disseminated plan that will address secure trade using strong agreements [20] in the light of blockchain innovation. The study investigated the use and variability of strict agreements to formulate a structured cycle of insurance organizations. Man-made artificial intelligence (AI) and AI structures can be incorporated into the areas of definition of case protection, customer support and improper identification. Contextual research was initiated on poor representation and high expectations in dealing with risks. In order to assess the level of premium and anticipate suspicious cases, a mining strategy was initiated. In addition to the premium rate, the chances of a false case were determined by three different team figures: J48, Naive Bayes and Random Backwoods. The study presented in used a rational, rational approach, which defines green AI calculation levels to increase robust recognition. The latter process was used to erroneously supply large and large-sized databases, using a recurring volume of participation. A strategy was proposed to protect medical services from fraud [21] to isolate patients. In addition, the difference between accidental robbery based on the closest models of neighbors hired in conjunction with conventional reality strategies was explored in where strategies based on distance, magnitude and comprehension were used to distinguish unequal occurrences. Accuracy measurements and F measurements were used to test the proposed model. Either way, in big data sets and finished information, this strategy makes no sense. One employee recommended an engine protection system to anticipate risky levels of customers, relying on fake neural networks [22]. This review refers to a forecasting model that can test customer protection engine. In [23] an in-depth study structure was developed for the assessment of human installments. The purpose of this work was to study the history of social cohesion, as well as to foresee their potential for social protection practices. In [24] it was proposed an in-depth engineering project to identify and reduce motor vehicle injuries. This work recommends the in-depth exchange and learning processes of car insurance agencies to distinguish motor vehicle injuries, locate them, and order their critical grades. Mask R-CNN methods have been used to detect injuries in vehicles.

3.
Motivation • The traditional system of vehicle insurance management involves huge man power and administrative works which produce high latency. • Each time new policy number gets modified so that the record maintenance gets complicated • Too much dependency on the customer side (Eg : New India Insurance ) They try to get all the details from the customer which may lead to details variation .

Proposed system
The proposed plan satisfies the expectations of both users and insurance companies for managing and maintaining insurance records and vehicle claim history. The whole project is done in the name of considering the context of one-page web-based applications for insurance archiving, making previous claim reports, data management and customer data management effective, etc. Figure 1 shows the Flowchart of insurance management application. Table 1 shows the List of sub-modules in Admin and Customer Module The prominent features of the proposed system are: • Provide an online platform for customers to check various policies available in the company.
• Apply/Renew a Policy using the website • Send Claim requests to the company • Insurance companies can use this system for effective usage of customer data, low latency retrieval , storage and management of claim history.

Algorithm 1 : Shortest Job First (SJF) Scheduling Algorithm
Shortest job after (SJN), also called the Shortest Task First (SJF) or the Shortest Work Next Phase (SPN), is a programmer coverage for running the smallest-time, waiting method. The shortest time each technique is expected to wait until it is complete, due to its simplicity and its average length of time. However, it has the potential for strategy hunger processes, such that even fast strategies are typically offered, they will take a long time to complete. The next optimum reaction ratio is close, but it gives way to this problem by using a way that is older.

Algorithm 2 : Reed Solomon Algorithm for Error Correction
The errors that occur due to distortion in image are rectified using Reed Solomon codes. The error information can be corrected before image production. The decoding logic of RS identifies the distortion in polynomial locator syndromes and corrects the values to overcome the error. Using this algorithm, we are generating QR codes for encoding the policy details and payment details in our application. From the performance evaluation it is clearly exhibited that the proposed system overcomes the flaws in the existing system. Figures 2-5 shows the results.

Conclusion
Finally, these all are the features included in our project. It provides both Insurance Company and Customers an easy way to manage the policies. The functionalities can also be enhanced in the future to increase the applicability and usability of the project. Currently it is only used for two wheeler and four wheeler further it can be expanded to heavy vehicles.