The problem of providing coverage using a group of mobile agents is investigated, where it is desired to minimize the overall coverage metric (service cost) while achieving maximum coverage with minimum actuator energy required by each agent. In addition, a distributed multi-agent area coverage control (MAACC) law is then provided which guarantees the convergence of agents to the optimal configuration with respect to the cost (coverage metric) function. A common assumption in all of the coverage control results is that the distribution of sensory information in the environment is known apriori by all agents. The proposed cooperative area coverage control framework is based on two interdependent tasks: (i) online learning of the coverage area and storing of the data in the form of a “probability map”; and (ii) utilization of the probability map (which is used as a search map) and other data collected to compute online a positional error trajectory (e(t)) for the agents to follow at specified sampling time steps. The group of agents is considered as being a group of autonomous agents which exchange data but ultimately make their own decisions based on the received data collected during an area coverage mission. In addition to the probability map, each agent in a multi-agent system transmits its position information to its neighbours and receives the same information from them. The agents possess the probability maps (made possible via time-varying density function) of targets
1) Modern patrol allocations will only be accurate if the data that is input is accurate; if the data is not accurate, then the allocation model results will also be inaccurate (Fritsch, Liederbach, Taylor & Caeti, 2009, pg. 41).
circuit commitment orders. The purpose of Levy Squad Operations has been to establish a facilitate standard procedure so Levy Squad deputies can effectively perform duties court-ordered executions and returns in accordance with established SCSO policy and procedure, in conformance with Tennessee law. Levy Squad collects city and county taxes on businesses (http://pnp.sheriff411.org/). In addition, the Levy Squad collects revenue on behalf of the plaintiff, confiscate property or anything of value to satisfy an execution. The Levy Squad also processes evictions, but the deputy’s presence was to maintain security of the realtor, moving crew, the occupant and any person involved in the eviction. The Order of Protection and Exparte Orders has emerged
Finally, the fifth program I will look at is Saturation Patrols. According to an FBI Law Enforcement Bulletin (2003), this DUI strategy involves “an increased enforcement effort targeting a specific geographic area to identify and arrest impaired drivers” (Greene, p.3). Through increased patrolling, Saturation Patrol officers are on constant lookout for signs of impaired drives such as swerving, “following too closely, reckless driving, aggressive driving, and speeding” (p. 3). Unlike sobriety checkpoints, Saturation Patrols gives officers a better chance of catching impaired drivers because officers are scattered throughout a high-risk area, increasing the likelihood an impaired driver would be caught. Also unlike sobriety checkpoints, this strategy does not offer drivers a way to avoid apprehension if they are impaired since they offer drivers the opportunity to avoid the checkpoints. To incorporate this patrol strategy, some departments require “documentation as to why a specific location was chosen [and s]elected sites should have a statistically high incidence of DUI crashes or fatalities and take into account officer and motorist safety” (p. 3).
Since starting in coverage team at Vecova, I have so far been able to successfully accomplish the following tasks in all the group homes I have worked: Implementation of clients’ service plan and review, assessment of clients’ daily services, identification, development, review and monitoring of risk management plans and report on client personal outcome
A module helicopter is required to assist the game reserve industry. The module should get the flight path form the headquarters and by using the auto pilot, it should follow the flight plan. This research concept is not new, but the concept has to be implemented more cost effectively, since available systems are not cost effective.
The evaluation of the proposed ADPP algorithm with comparison with previous approaches Centralized prioritized planning (CPP) and SDPP is done. The evaluated runtime characteristics of the algorithms is the wall clock run time, communication complexity (the number of broadcasted messages) and solution quality. In the evaluated problem s number of Robots varies from 30 to 100. The average wall clock run time are depicted in figure 1a. The results show that the decentralized algorithms requires less run time than the centralized algorithm. Further, the ADPP performs better than the SDPP. The required number of exchanged messages are plotted in figure1b.For communication complexity for less than 60 robots decentralized algorithms outperform the centralized algorithms. The communication complexity of the decentralized algorithms start exceeding the centralized algorithms for more than 60 robots. The figure 1c shows the average costs. The
Abstract -- The efficiency of sensor networks depends on the coverage of the target area. Although, in general, a sufficient number of sensors are used to ensure a certain degree of redundancy in coverage, a good sensor deployment method is still necessary to balance the workload of sensors in target area. In a sensor network sensors can move around to self-deploy. The deployment deals with moving sensors from an initial unbalanced state to balanced state. Therefore, several optimization problems can be defined to minimize different parameters such as total moving distance, number of moves, communication cost. There is a unique problem called communication holes in sensor networks, areas not covered by any node.
The work has been able to verify that the number of mobile cellular network operators who can effectively share infrastructure on a base station is limited by the following parameters:
[5] used a genetic algorithm to optimize the locations of UAVs to improve the throughput coverage and the fifth-percentile throughput of the network. Researchers in [6] identified main disaster management applications of UAVs and discussed some open research issues. They showed that UAV networks in conjunction with WSN and cellular network are promising future technology for the applications in disaster management. [7] used SysML-Sec/TTool for formal verification of safety and security of an autonomous UAV mission. They modelled the embedded and communication system of the UAV as well as the processing performed by the central computer controlling the UAV. [8] described cross-platform application and algorithm for handling
Even though the efficiency is greatly improved, our framework is still impractical in the sense that the process can be further prolonged with 1) a even higher availability requirement, which is normal in a carrier-class network [18] (usually requires an availability of 99.999% or 99.9999% (5’9s or 6’9s)); 2) more requests; and 3) longer contract period duration. The root cause the process takes such a long time is it depends on the strategy we use to provision backups and how many backups are needed. In other words, if we can accurately estimate the least possible number of backups needed without running the trial-and-error process, a great amount of running time can be saved. The process
Due to limited and non-rechargeable energy provision, the energy resource of sensor networks should be managed wisely to extend the lifetime of sensors. Sensor networks have recently emerged as a platform for several important surveillance and control applications .Each sensor has an onboard radio that can be used to send the collected data to interested parties. One of the advantages of wireless sensors networks (WSNs) is their ability to operate unattended in harsh environments in which contemporary human-in-the-loop monitoring schemes are risky, inefficient and sometimes infeasible. Therefore, sensors are expected to be deployed randomly in the area of interest by a relatively uncontrolled means, e.g. dropped by a helicopter, and to collectively form a network in an ad-hoc manner. In order to achieve high energy efficiency and increase the network scalability, sensor nodes can be organized into clusters. Data collected from sensors are sent to the cluster head first, and then forwarded to the base station. Network lifetime can be defined as the time elapsed until the first node (or the last node) in the network depletes its energy (dies).
Now that we know our pizza delivering drone is flight ready we will move on to the in-flight performance monitoring. Our expert remote operator pilots will man the controls from the beginning to the end of the flight, closely watching the camera feed as well as the GPS position on a moving map. The drone will be flown autonomously, but if for any reason something were to go wrong, the remote pilot will be able to take over. During the flight there will be several hazards to watch out for including people, obstructions (buildings, signs, etc.). By using the feed from the camera, the remote pilot will be able to avoid the majority of them, and by planning out routes that avoid populated areas, we will be able to negate even more of those hazards. Other factors to consider are potential system failures and airspace. Knowing where our sUAS is at all times is key to any malfunction that goes wrong, our organization needs to be able to quickly retrieve the sUAS and deliver the pizza without hindering the customer. When mitigating airspace confusion, it is always best to plan ahead. Our pre-determined routes will be crosschecked with the FAA’s latest maps and charts, making sure to stay 5 miles away from any airport.
To develop a sustainable business that is profitable for the company, agents and the clients.
Abstract— Mobile ad hoc networks will appear in environments where the nodes of the networks are absent and have little or no physical protection against tampering. The nodes of mobile ad hoc networks are thus susceptible to compromise. The networks are particularly vulnerable to denial of service (DOS) attacks launched through compromised nodes or intruders. This work proposed a new DOS attack and its defense in ad hoc networks. The new DOS attack, called Ad Hoc Flooding Attack(AHFA), can result in denial of service when used against on-demand routing protocols for mobile ad hoc networks, such as AODV, DSR.
PRM has a powerful way to track the planning of robot’s movement. PRM is to specimen at random a robot’s configuration space, and relates the Samples points to build a graph of the road map, which picks up the call of free space, PRM used in the implementation of many, in addition to robots, including virtual models and computational biology. In this paper, a probabilistic roadmap method of path planning for mobile robot is proposed to use it in Known environment.