Evaluating Uncertainty of Measurement While Predicting Location in Smart Vehicles

MAPAN ◽  
2021 ◽  
Author(s):  
Sudesh Pahal ◽  
Neeru Rathee
2015 ◽  
Vol 39 (2) ◽  
pp. 199-202
Author(s):  
Wojciech Batko ◽  
Renata Bal

Abstract The assessment of the uncertainty of measurement results, an essential problem in environmental acoustic investigations, is undertaken in the paper. An attention is drawn to the - usually omitted - problem of the verification of assumptions related to using the classic methods of the confidence intervals estimation, for the controlled measuring quantity. Especially the paper directs attention to the need of the verification of the assumption of the normal distribution of the measuring quantity set, being the base for the existing and binding procedures of the acoustic measurements assessment uncertainty. The essence of the undertaken problem concerns the binding legal and standard acts related to acoustic measurements and recommended in: 'Guide to the expression of uncertainty in measurement' (GUM) (OIML 1993), developed under the aegis of the International Bureau of Measures (BIPM). The model legitimacy of the hypothesis of the normal distribution of the measuring quantity set in acoustic measurements is discussed and supplemented by testing its likelihood on the environment acoustic results. The Jarque-Bery test based on skewness and flattening (curtosis) distribution measures was used for the analysis of results verifying the assumption. This test allows for the simultaneous analysis of the deviation from the normal distribution caused both by its skewness and flattening. The performed experiments concerned analyses of the distribution of sound levels: LD, LE, LN, LDWN, being the basic noise indicators in assessments of the environment acoustic hazards.


Telecom ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 108-140
Author(s):  
Paulo Álvares ◽  
Lion Silva ◽  
Naercio Magaia

It had been predicted that by 2020, nearly 26 billion devices would be connected to the Internet, with a big percentage being vehicles. The Internet of Vehicles (IoVa) is a concept that refers to the connection and cooperation of smart vehicles and devices in a network through the generation, transmission, and processing of data that aims at improving traffic congestion, travel time, and comfort, all the while reducing pollution and accidents. However, this transmission of sensitive data (e.g., location) needs to occur with defined security properties to safeguard vehicles and their drivers since attackers could use this data. Blockchain is a fairly recent technology that guarantees trust between nodes through cryptography mechanisms and consensus protocols in distributed, untrustful environments, like IoV networks. Much research has been done in implementing the former in the latter to impressive results, as Blockchain can cover and offer solutions to many IoV problems. However, these implementations have to deal with the challenge of IoV node’s resource constraints since they do not suffice for the computational and energy requirements of traditional Blockchain systems, which is one of the biggest limitations of Blockchain implementations in IoV. Finally, these two technologies can be used to build the foundations for smart cities, enabling new application models and better results for end-users.


Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 955
Author(s):  
Zhiyuan Li ◽  
Ershuai Peng

With the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay. Recently, vehicular computation-intensive task offloading has become a new research field for the vehicular edge computing networks. However, dynamic network topology and the bursty computation tasks offloading, which causes to the computation load unbalancing for the VEC networking. To solve this issue, this paper proposed an optimal control-based computing task scheduling algorithm. Then, we introduce software defined networking/OpenFlow framework to build a software-defined vehicular edge networking structure. The proposed algorithm can obtain global optimum results and achieve the load-balancing by the virtue of the global load status information. Besides, the proposed algorithm has strong adaptiveness in dynamic network environments by automatic parameter tuning. Experimental results show that the proposed algorithm can effectively improve the utilization of computation resources and meet the requirements of computation and transmission delay for various vehicular tasks.


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