Gurdit Singh

Safety issues while driving in smart cities are considered to be top-notch priority in contrast to traveling. Today’s fast paced society, often leads to accidents. In order to reduce the road accidents, one key area of research is monitoring the driving behavior of drivers. Understanding the driver behavior is an essential component in Intelligent Driver Assistance Systems. One of potential cause of traffic fatalities is aggressive driving behavior. However, drivers are not fully aware of their aggressive actions. So, in order to increase awareness and to promote driver safety, a novel system has been proposed. In this work, we focus on DTW based event detection technique, which have not been researched in motion sensors based time series data to a great extent. Our motivation is to improve the classification accuracy to detect sudden braking and aggressive driving behaviors using sensory data collected from smartphone. A very significant feature of DTW is to be able to automatically cope with time deformations and different speeds associated with time-dependent data which makes it suitable for our chosen application where data might get affected due to factors such as: high variability in road and vehicle conditions, heterogeneous smartphone sensors, etc. Our technique is novel as it uses fusion of sensors to enhance detection accuracy. The experimental results show that proposed algorithm outperforms the existing machine learning and threshold-based techniques with 100% detection rate of braking events and 97% & 86.67% detection rate of normal left & right turns and aggressive left & right turns respectively.

Road surface monitoring is an important problem in providing smooth road infrastructure to the commuters. The key to road condition monitoring is to detect road potholes and bumps, which affect the driving comfort and transport safety. This paper presents a smartphone based sensing and crowdsourcing technique to detect the road surface conditions. The in-built sensors of the smartphone like accelerometer and GPS1 have been used to observe the road conditions. It has been observed that several techniques in the past have been proposed using these sensors. Such techniques either use fixed threshold values which are road or vehicle condition dependent or use machine learning based classified training which requires intensive and continuous training. The motivation of our work is to improve classification accuracy of detecting road surface conditions using DTW2 technique which has not been researched on data based on motion sensors. The main features of DTW is its ability to automatically cope with time deformations and different speeds associated with time data, its simplicity is to be used in resource constrained devices such as smartphones and also the simplicity in its training procedure which is must as fast as compared to techniques such as SVM,3 HMM4 and ANN.5 Our technique shows better accuracy and efficiency with detection rate of 88.66% and 88.89% for potholes and bumps respectively, when compared with the existing techniques With the use of the proposed technique, prioritization of the road repair and maintenance can be decided based on real-time data and facts.

In recent years, mesh networking has emerged as a key technology for the last mile Internet access and found to be an important area of research and deployment. The current draft standard of IEEE 802.11s has defined routing for Wireless Mesh Networks (WMNs) in layer-2 and is termed as Hybrid Wireless Mesh Protocol (HWMP). However, security in routing or forwarding functionality is not specified in the standard. As a consequence, HWMP in its current from is vulnerable to various types of routing attacks such as flooding, route disruption and diversion, spoofing etc. In this paper, we propose a secure HWMP routing protocol for WMN. The proposed protocol uses cryptographic extensions to provide authenticity and integrity of HWMP routing messages and prevents unauthorized manipulation of mutable fields in the routing information elements. We will show that the proposed protocol successfully thwarts all the identified attacks.

To become independent of backbone networks leading to cheap deployments, the traditional single-hop approach needs to be replaced by Wireless Mesh Networks (WMNs). Wireless Mesh Networks is cost-effective alternative to wireless local area networks. Due to multi hop networking, WMN requires multi hop routing protocol. Mostly the nature of data is from client to gateway and vice versa. So, according to IEEE 802.11s Draft 3.0, HWMP routing protocol is adopted. In this paper, we analyzed the throughput of HWMP protocol with increase in number of nodes and increase in size of packets using simulation model.