Car-to-Cloud Communication Traffic Analysis Based on the Common Vehicle Information Model

Although connectivity services have been introduced already today in many of the most recent car models, the potential of vehicles serving as highly mobile sensor platform in the Internet of Things (IoT) has not been sufficiently exploited yet. The European AutoMat project has therefore defined an open Common Vehicle Information Model (CVIM) in combination with a cross-industry, cloud-based big data marketplace. Thereby, vehicle sensor data can be leveraged for the design of entirely new services even beyond traffic-related applications (such as localized weather forecasts). This paper focuses on the prediction of the achievable data rate making use of an analytical model based on empirical measurements. For an in-depth analysis, the CVIM has been integrated in a vehicle traffic simulator to produce CVIM-complaint data streams as a result of the individual behavior of each vehicle (speed, brake activity, steering activity, etc.). In a next step, a simulation of vehicle traffic in a realistically modeled, large-area street network has been used in combination with a cellular Long Term Evolution (LTE) network to determine the cumulated amount of data produced within each network cell. As a result, a new car-to-cloud communication traffic model has been derived, which quantifies the data rate of aggregated car-to-cloud data producible by vehicles depending on the current traffic situations (free flow and traffic jam). The results provide a reference for network planning and resource scheduling for car-to-cloud type services in the context of smart cities

INTERNET OF THING BASED CAR PARKING SYSTEM

In the current era, we are facing a new problem of parking of vehicles. It is a major problem in urban cities. The problem is more tough because of continues growing number of vehicle and also size of vehicles. Car parking is not just a major problem in India but also in all over the world. We know that one million vehicles burn oil every day. In this paper, we propose an automatic and real-time system for automated car parking. This system would be implemented by the use of internet of things (IOTs). IOT refers as any physical thing that is connected to internet or exchanging information or data between internet and physical device. Arduino Uno is a microcontroller used in IOT. It is used for building digital devices, and interactive objects that can sense and control physical devices. Our smart parking will be implementing using Arduino Uno board for car parking and Ethernet shield to connect parking area with web or internet. By using our automated parking system, a user can save much time for searching free parking space. An infrared sensor has to be employed in each slot to check that a particular plot is vacant or not. Searching smart parking system helps people to search parking space accessible with the ease of IOT automation by supplying parking slot free information. The user can book in advance the parking slot and update the information to the server. Every user has a unique id and password. In case a car in stolen and enter the parking IOT the server checks the database and inform the police.Â

Vehicular Data Cloud Services

The advance cloud computing has provided an opportunity to resolve the challenges which effects by increasing transportation issues. Two methods of cloud services are available these are parking and mining. Mobile cloud computing has improved the storage capacity, stand by time of mobile terminals by migrating data processing to the remote cloud. The introduction of smart phones, cloud computing the automotive system is shifting toward the internet of vehicles

Novel Common Vehicle Information Model (CVIM) for Future Automotive Vehicle Big Data Marketplaces

Even though connectivity services have been introduced in many of the most recent car models, access to vehicle data is currently limited due to its proprietary nature. The European project AutoMat has therefore developed an open Marketplace providing a single point of access for brand-independent vehicle data. Thereby, vehicle sensor data can be leveraged for the design and implementation of entirely new services even beyond trafficrelated applications (such as hyper-local traffic forecasts). This paper presents the architecture for a Vehicle Big Data Marketplace as enabler of cross-sectorial and innovative vehicle data services. Therefore, the novel Common Vehicle Information Model (CVIM) is defined as an open and harmonized data model, allowing the aggregation of brand-independent and generic data sets. Within this work the realization of a prototype CVIM and Marketplace implementation is presented. The two use-cases of local weather prediction and road quality measurements are introduced to show the applicability of the AutoMat concept and prototype to non-automotive applicatio

A Fog-based Distributed Look-up Service for Intelligent Transportation Systems

Future intelligent transportation systems and applications are expected to greatly benefit from the integration with a cloud computing infrastructure for service reliability and efficiency. More recently, fog computing has been proposed as a new computing paradigm to support low-latency and location-aware services by moving the execution of application logic on devices at the edge of the network in proximity of the physical systems, e.g. in the roadside infrastructure or directly in the connected vehicles. Such distributed runtime environment can support low-latency communication with sensors and actuators thus allowing functions such as real-time monitoring and remote control, e.g. for remote telemetry of public transport vehicles or remote control under emergency situations, respectively. These applications will require support for some basic functionalities from the runtime. Among them, discovery of sensors and actuators will be a significant challenge considering the large variety of sensors and actuators and their mobility. In this paper, a discovery service specifically tailored for fog computing platforms with mobile nodes is proposed. Instead of adopting a centralized approach, we pro-pose an approach based on a distributed hash table to be implemented by fog nodes, exploiting their storage and computation capabilities. The proposed approach supports by design multiple attributes and range queries. A prototype of the proposed service has been implemented and evaluated experimentally

Framework for propagating stress control message using heartbeat based IoT remote monitoring analytics

Abnormal level of stress is the root indicator factor to have significant impact over the health of heart and there is a close relationship between the stress levels with heart rate. Review of the existing literature showcase that there has been various work that has been carried out towards investigation of considering heart rate with an internet-of-things (IoT) system. Apart from this, existing system doesnt offer any instantaneous solution where certain intimation is offered in real-time to the user with wearables as a solution to control the stress condition. Therefore, the current paper introduces a novel framework where the sampled heart rates of the patients are captured by IoT deivices. The aggregated data are further forwarded to the cloud analytic system that uses correlation to extract the appropriate message. The system after being applied with teh machine learning approach could further extract the elite outcome followed by forwarding the contextual data to teh user. Using an analytical modelliig, the proposed system shows that it offers better accuracy and reduced processing time when compared with other machine learning approach and thereby it proves to be cost effective solution in IoT system over medical case study

DATA ACQUISITION SYSTEM USING IN MOBILE APPLICATION

The scope of the project would be to create a sensor interface device required for sensor data assortment of industrial atmosphere We by hand measure physical parameters in the market like temperature, humidity, level, Co2, moisture sensor and lightweight recognition that is very hard and inaccurate. An ordinary person cannot appraise the physical parameters precisely. To avert this difficulty we opting for our suggested system in which the wireless connection is carried out to acquire data in the various sensors, additionally it cuts down on setup difficulties. By utilizing Bluetooth Technology, sensors information is delivered to the approved person, who is able to begin to see the data status on Smartphone through Android Application. The work is aimed to create an alarm system which could monitor the various sensors to get Industrial parameters like smoke and temperature and transmit the information towards the approved person using Bluetooth communication technology. The main benefit of this PROJECT is supplying the safety for data while transmitting and sensing the sensor Values very precisely

A Security Situation Awareness Approach for IoT Software Chain Based on Markov Game Model

Since Internet of Things (IoT) has been widely used in our daily life nowadays, it is regarded as a promising and popular application of the Internet, and has attracted more and more attention. However, IoT is also suffered by some security problems which seriously affect the implementation of IoT system. Similar to traditional software, IoT software is always threated by many vulnerabilities, thus how to evaluate the security situation of IoT software chain becomes a basic requirement. In this paper, A framework of security situation awareness for IoT software chain is proposed, which mainly includes two processes: IoT security situation classification based on support vector machine and security situation awareness based on Markov game model. The proposed method firstly constructs a classification model using support vector machine (IoT) to automatically evaluates the security situation of IoT software chain. Based on the situation classification, we further proposed to adopt Markov model to simulate and predict the next behaviors of participants that involved in IoT system. Additionally, we have designed and developed a security situation awareness system for IoT software chain, the developed system supports the detection of typical IoT vulnerabilities and inherits more than 20 vulnerability detection methods, which shows great potential in IoT system protection