Use of Smartphones for Rapid Location Tracking in Mega Scale Soil Sampling

Conventional, grid-based sampling location tracking approach with GPS or topographic maps is time-consuming and inconvenient. Therefore, this study combined the freely available virtual/digital globe with recent advancements of smartphone geo-browsers to develop a new sampling location tracking approach. The sampling frame was developed with pre-uploaded point map formulated in GIS environment by combining land-use map and one-kilometer grid with center coordinates. The sampling location grid was uploaded to smartphone and each point was tracked with Google Map path finder using point ID (coded grid coordinate) when searching each sampling location. The suitability of the new approach was tested for soil sample collection from paddy lands distributed in 0.9 million hectares in Sri Lanka. The sampling locations could be reached conveniently with the help of Google path-finder voice direction guide and optional routes. The efficiency of new approach was found to be remarkably high, i.e., over 99% of the 9000 sampling points, which were spread across Sri Lanka having an area of 65,610 km2. All sampling points in the country could be covered with twelve member field investigation crew who were guided through smartphones uploaded with sampling point grid on six motorbikes within 60 days. The new sampling location tracking approach is effective in terms of cost, time, human resource requirements, thus can be adopted in large-scale soil/plant sampling frames with high accuracy.

Real-time localization for underwater equipment using an extremely low frequency electric field

A new real-time underwater equipment location method adopting an electric field induced by a standard current source is proposed.Our goals were real-time tracking and location of stationary or moving underwater equipment both in shallow and deep seas,under noisy conditions.The main features of this method are as follows:(1)a standard current source on the water surface,which can be towed by a vehicle,consisting of two electrodes,a signal generator,and a GPS unit;(2)measurement of the extremely low frequency(ELF)electric field emitted by the current source,made possible by electric field sensors on the underwater equipment;(3)position of the underwater equipment is estimated in real time based on a progressive update extended Kalman filter(PUEKF),which is carried out using the propagation model of an ELF electric field because the electric field at the position of the underwater equipment and the current source position are known.We verified the accuracy of our method and confirmed real-time location feasibility through numerical,physical scale,and real-time sea experiments.Through numerical experiments,we verified that our method works for underwater equipment location in real-world conditions,and the location error can be less than 0.2 m.Next,real-time location experiments for stationary underwater measuring equipment in water tank were conducted.The result shows that the location error can be less than 0.1 m.We also confirmed real-time location feasibility through the use of offshore experiment.We expect that our method will complement conventional underwater acoustic location methods for underwater equipment in acoustically noisy environments.

SPATIAL TRAJECTORY PREDICTION OF VISUAL SERVOING

Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.

Adaptive beaconing for collision avoidance and tracking accuracy in vehicular networks

In vehicular networks,the exchange of beacons among neighboring vehicles is a promising solution to guarantee a vehicle's safety.However,frequent beaconing under high vehicle density conditions will cause beacon collisions,which are harmful to a vehicle's driving safety and the location tracking accuracy.We propose an ABIwRC(Adaptive Beaconing Interval with Resource Coordination)method for a highway scenario.Each vehicle broadcasts beacon interval requests,including the intervals needed for both the vehicle's driving safety and location tracking accuracy.The RSU(Road Side Unit)allocates resources for a vehicle's beaconing according to the requests from all vehicles and the interference relationship between the vehicles in adjacent RSUs.We formulate a resource allocation problem for maximizing the sum utility,which measures the satisfaction of vehicles'requests.We then transform the optimization problem into a maximum weighted independent set problem,and propose an algorithm to solve this effciently.Simulation results show that the proposed method outperforms the benchmark in terms of beacon reception ratio,vehicle driving safety,and location tracking accuracy.

Architecture for mobile group communication in campus environment

The demand for group communication using smart devices in campus environment is increasing rapidly. In this paper, we design an architecture for a mobile group communication system （MGCS） on campus by using Wi-Fi networks and smart devices. The architecture is composed of a web-based system and a smart device based mobile system. Through the systems, users on campus create community/mobile group, maintain dynamic group membership, and reliably deliver the message to other users. We use the common features of many smart devices to develop a prototype that works on off-the-shelf hardware. In the experimental section, we demonstrate our system using various real scenarios which can occur in university campuses.