Speed is one of the basic reasons for vehicle accident. Many lives could have been saved if emergency service could get accident information and reach in time. Nowadays, GPS has become an integral part of a vehicle system. This paper proposes to utilize the capability of a GPS receiver to monitor speed of a vehicle and detect accident basing on monitored speed and send accident location to an Alert Service Center. The GPS will monitor speed of a vehicle and compare with the previous speed in every second through a Microcontroller Unit. Whenever the speed will be below the specified speed, it will assume that an accident has occurred. The system will then send the accident location acquired from the GPS along with the time and the speed by utilizing the GSM network. This will help to reach the rescue service in time and save the valuable human life.

Accident detection and reporting system using GPS, GPRS and GSM technology

3D local surface description is now at the core of many computer vision technologies, such as 3D object recognition, intelligent driving, and 3D model reconstruction. However, most of the existing 3D feature descriptors still suffer from low descriptiveness, weak robustness, and inefficiency in both time and memory. To overcome these challenges, this paper presents a robust and descriptive 3D Binary Shape Context (BSC) descriptor with high efficiency in both time and memory. First, a novel BSC descriptor is generated for 3D local surface description, and the performance of the BSC descriptor under different settings of its parameters is analyzed. Next, the descriptiveness, robustness, and efficiency in both time and memory of the BSC descriptor are evaluated and compared to those of several state-of-the-art 3D feature descriptors. Finally, the performance of the BSC descriptor for 3D object recognition is also evaluated on a number of popular benchmark datasets, and an urban-scene dataset is collected by a terrestrial laser scanner system. Comprehensive experiments demonstrate that the proposed BSC descriptor obtained high descriptiveness, strong robustness, and high efficiency in both time and memory and achieved high recognition rates of 94.8%, 94.1% and 82.1% on the considered UWA, Queen, and WHU datasets, respectively.

A novel binary shape context for 3D local surface description

All people experience aging, and the related physical and health changes, including changes in memory and brain function. These changes may become debilitating leading to an increase in dependence as people get older. Many external aids and tools have been developed to allow older adults and elderly patients to continue to live normal and comfortable lives. This mini-review describes some of the recent studies on cognitive decline and motor control impairment with the goal of advancing non-invasive brain computer interface (BCI) technologies to improve health and wellness of older adults and elderly patients. First, we describe the state of the art in cognitive prosthetics for psychiatric diseases. Then, we describe the state of the art of possible assistive BCI applications for controlling an exoskeleton, a wheelchair and smart home for elderly people with motor control impairments. The basic age-related brain and body changes, the effects of age on cognitive and motor abilities, and several BCI paradigms with typical tasks and outcomes are thoroughly described. We also discuss likely future trends and technologies to assist healthy older adults and elderly patients using innovative BCI applications with minimal technical oversight.

/pdf/brain-computer-interfaces-for-improving-the-quality-of-life-19wkdm4ykw.pdf

Brain Computer Interfaces for Improving the Quality of Life of Older Adults and Elderly Patients.

Local voxelized structure for 3D binary feature representation and robust registration of point clouds from low-cost sensors

In this paper, a global descriptor for a LiDAR point cloud, called LiDAR Iris, is proposed for fast and accurate loop-closure detection. A binary signature image can be obtained for each point cloud after several LoG-Gabor filtering and thresholding operations on the LiDAR-Iris image representation. Given two point clouds, their similarities can be calculated as the Hamming distance of two corresponding binary signature images extracted from the two point clouds, respectively. Our LiDAR-Iris method can achieve a pose-invariant loop-closure detection at a descriptor level with the Fourier transform of the LiDAR-Iris representation if assuming a 3D (x,y,yaw) pose space, although our method can generally be applied to a 6D pose space by re-aligning point clouds with an additional IMU sensor. Experimental results on five road-scene sequences demonstrate its excellent performance in loop-closure detection.

LiDAR Iris for Loop-Closure Detection

Detecting keypoint sets on 3D point clouds via Histogram of Normal Orientations

Various research studies conducted all around the world reveal that 75% of people with debilitating physical disabilities and elderly people experience significant difficulties for their day to day locomotion. Although there are existing solutions to overcome this problem, none of them served to be customizable, economical and user friendly all at the same time. Therefore, one of the best options that could be useful for these affected class of people is a gesture-based interaction with their environment, in particular their wheelchairs. The proposed system named as 'Gest-BOT', uses a small camera mounted very close to the user's hand, which tracks the small movements of their fingers to understand the direction of movement of the wheelchair. A gesture recognition system which identifies the gesture is then interfaced to the wheelchair control system in order move it to the desired location. Gest-BOT is effortless to use, customizable, economical, highly convenient and non-intrusive. The hardware implementation of Gest-BOT consists of a wheelchair, an Arduino board based ATmega microcontroller and an Intel Atom EBC-352 processor, which uses MATLAB® executables for gesture image processing. We have also calculated the response of the system under various conditions which is detailed in the paper.

https://www.amrita.edu/system/files/publications/gest-bot-highly-convenient-locomotive-solution-elderly-physically-challenged.pdf

'Gest-BOT' - A Highly Convenient Locomotive Solution for the Elderly and Physically Challenged

In this paper, we propose an Intelligent Home Navigation System (IHNS) which comprises of a wheelchair, voice module and navigation module. It can be used by an elderly or physically challenged person to move inside the home without any difficulty. It's common that the elders forget the way to the different rooms in house and the physically challenged people find it hard to move the wheel chair without external aid. By making use of IHNS, elderly and the physically challenged can go to different rooms in the house like kitchen, living room, dining room etc by just speaking a word which is predefined to that particular room. The voice of the person is detected by voice capture module which will be compared by voice recognition module with predefined voices loaded in to the system. According to the received voice, the destination is automatically understood and the wheelchair moves according to the route which is predefined. It is also equipped with obstacle avoidance technique, where the person may not be able to provide proper voices at the right time. The wheel chair can automatically navigate from one point to the other in the home as per predefined route based on the voice received. Thus the above proposed system can be used by elderly and physically challenged people in day to day life even if they are alone at home.

Automated voice based home navigation system for the elderly and the physically challenged

With the availability of commodity depth sensors and depth sensing capabilities on mobile devices, there is a need to develop memory efficient and computationally cheap applications. 3D feature descriptor based keypoint matching is the very first step in various computer vision and robotic applications, and is also one of the most memory and computationally demanding steps. In this work, we apply Principal Component Analysis (PCA) to reduce the dimensionality of 3D feature descriptors and show that they retain their descriptiveness, while drastically decreasing their memory and computational requirements. We apply this scalable PCA based dimensionality reduction technique on three state-of-the-art 3D feature descriptors and quantitatively evaluate their performance with varying dimensionality. Experimental results on publicly available Bologna Kinect dataset show that the proposed method reduces the dimensionality of SHOT, RoPS and FPFH feature descriptors from 352 to 50, 135 to 30 and 33 to 15, respectively, while offering more than 90% of the keypoint matching performance.

On creating low dimensional 3D feature descriptors with PCA

In this paper, we suggest a Low Power Intelligent, Wireless, Home Security System (IWHSS) for Elders. The elders can avail the services of this IWHSS, conveniently within their room. If the elder is uncomfortable with a stranger trying to get into the home, services of IWHSS can be availed. The strangers can be identified and in emergency situations where the elder feels the necessity of the external help, the police and relatives can be informed via IWHSS. In addition to informing the police, the system also activates an emergency alarm to alert the neighbors. The elders can also see the stranger at the door and make a conversation with them. The system uses GPRS Modem which is interfaced directly with PIC 16F877A microcontroller to make the system power efficient. We have used low cost RF modules, PIC 16F877A microcontroller, IR-TSOP modules and Image Capture module as part of the hardware implementation of the system. The simulation software's used were MPLAB IDE and PROTEUS.

https://www.amrita.edu/system/files/publications/low-power-intelligent-wireless-home-security-system-elderly-people.pdf

Sai Manoj Prakhya

Papers

Detecting keypoint sets on 3D point clouds via Histogram of Normal Orientations

'Gest-BOT' - A Highly Convenient Locomotive Solution for the Elderly and Physically Challenged

Automated voice based home navigation system for the elderly and the physically challenged

On creating low dimensional 3D feature descriptors with PCA

Low power, intelligent, wireless, home security system for the elderly people