Applications:

The mobile agent technology can significantly enhance the design
and analysis of problem domains under the following three circumstances.
(1) the problem domain is geographically distributed;
(2) the subsystems exist in a dynamic environment; (3)
the subsystems need to interact with each other more flexibly.
Mobile agents can travel
between different execution environments. Mobile agents
can be created dynamically at runtime and dispatched to
source systems to perform tasks with the most updated code.
Therefore, the mobility of mobile agents provides distributed applications
with significant flexibility and adaptability in
dynamically changing environments.
Mobile-C is a general mobile agent platform,
it can find its applications in many areas, especially in
networked intelligent mechatronic and embedded systems.
For example, when dealing with terra mining or planet
exploration where multiple mobile units are required to setup
equipment or explore the environment, the mobile units are far from
the control center and communication is delayed or nonexistent.
Intelligent autonomous agent-based systems can collaborate in order
to overcome obstacles without the need for continued supervision from
the control center. As another example,
the ability to
travel allows mobile agent systems to move computation to
source systems.
This decentralized approach improves network efficiency
since the processing is performed locally.
To add your application on this page,
please send a brief description of your project and web site
to
mobilec(@)ucdavus.edu
|
Agent-based real-time traffic detection and management system (ABRTTDMS) is an IEEE FIPA compliant multi-agent application aimed at providing real-time traffic conditions, predicting potential incidents, and alarming the predefined events to the traffic management center (TMC). The real-time traffic information detected by the system can also be used as the source of intelligent traveler information systems, which provide information, such as travel time, to travelers.
|
|
The Khepera 3 mobile robot is used for inter-agent communication in multi-robot colloboration-based testing.
|
|
The iRobot Create is a newly releaed iRobot system based on the widely
used Rhoomba robot. The Create has a more versatile interface making
it ideal for mobile robot research. The processing and intelligence
of the Create has been augmented through the use of a Gumstix computer.
|
|
The robot workcell consists of two robots Puma 560 and IBM 7575, and a conveyer system. The retrofitted robot controller consists of servo controller, I/O and A/D interface boards from Delta Tau Data Systems, machine vision system from Datacube and Panasonic, force/torque sensing system from JR3.
|
|
Vision systems have become popular for remote vision sensing in
geographically distributed environments due to the vast amount
of information they provide.
Mobile agent technology is a salient solution in vision sensor
fusion since it increases power efficiency by reducing
communication requirements and increases fusion processing by
allowing in-situ integration of on-demand visual processing
and analysis algorithms.
Mobile agents can dynamically migrate between multiple vision
sensors and combine necessary sensor data in a manner
specific to the requesting system.
|
|
In this sensor data acquisition experiment, an accelerometer is attached to
one surface of a running DC motor and also connected to a gumstix computer.
A mobile agent is sent from a local host to the gumstix to get raw data from
the accelerometer and process the raw data to produce accelerations in X and
Y directions.
The acceleration data are carried back by the mobile agent and displayed on
the local host.
|
Parallel computing is widely adotped in scientific and engineering
applications to enhance the efficiency.
Moreover, there are increasing research interests focusing on utilizing
distributed networked computers for parallel computing.
The Message Passing Interface (MPI) standard was designed to support
portability and platform independence of a developed parallel program.
However, the procedure to start an MPI-based parallel computation among
distributed computers lacks autonomicity and flexibility.
An autonomic dynamic parallel computing framework is presented which
provides autonomicity and flexibility that are important and necessary to
some parallel computing applications involving resource constrained and
heterogeneous platforms.
In this framework, an MPI parallel computing environment consisting of
multiple computing entities is dynamically established through inter-agent
communications using the IEEE Foundation for Intelligent Physical Agents
(FIPA) compliant Agent Communication Language (ACL) messages.
For each computing entity in the MPI parallel computing environment, a
load-balanced MPI program C source code along with the MPI environment
configuration statements are dynamically composed as a mobile agent code.
A mobile agent, wrapping the mobile agent code, is created and sent to the
computing entity where the mobile agent code is retrieved and
interpretively executed.
An example of autonomic parallel matrix multiplication is used to
demonstrate the self-configuration and self-optimization properties of
the presented framework.
|
Distributed Multi-Camera Surveillance for Intelligent Home

This project foresees the enlargement of an existing single-source
surveillance system, developed at our lab, to a distributed
multi-camera video network. Currently, the single-camera video
system is applied for fall detection in the so-called Video-Based
Intelligent Home (ViBIH). The main goal is thus to improve the
accuracy of the fall detection results and, at the same time,
enhance the vision field. Since we envision to use smart cameras,
where the primary image processing is performed close to the image
sensor, the main challenges faced by this project are: (i) the
video sensor units' connectivity, and (ii) the communication
network. As mentioned above, (i) comprises the process
synchronization and the cooperative integration of the multiple
video productions. It requires thus the definition of an
appropriate data structure, the development of the target
algorithms for merging and processing of the correlated info
coming from different video sources, as well as the
prioritization of related tasks. On the other hand, (ii)
includes the definition of the communication protocol and the
memory management policy.
In this project, Mobile-C is used in a multi-camera platform to
decentralize some of detection algorithms. For example, a human tracking algorithm will move from one smart camera to the other when the target move to the field of
vision of another camera. The algorithm is deployed in a mobile agent in Mobile-C.
http://www.he-arc.ch
Monitoring Intrusion detection on MANET using intelligent agent
Mesh Router Management with Mobile-Agent in Wireless Mesh Networks
Distributed SCADA system
Distributed Real-time Embedded Computing
An Urban Traffic Signal Control Systems
Based on Mobile Multi-Agent Technology
Using Adaptable Mobile Agents to Add QoS in Wireless Sensor Networks

Wireless sensor networks (WSN) are increasingly being used for critical
safety monitoring systems.
In these systems, the reliability level for the data is of paramount
importance especially when emergency situations occur and may involve
material and life losses.
Therefore, it is important that every incident can be tracked down
throughout the event.
Clearly, the information flow from the sensors, in these environments,
should continuously feed a monitoring system throughout the incident.
Moreover, monitoring all phases of the incident can be used for further
investigation and future prevention by revealing the source of the
problem.
It also helps the rescue team in the action management and in the
decision-making.
Typical video monitoring systems do not have all these features,
due to the lack of sensing feedback of what is happening in the
physical environment.
Thus, there is no way to know exactly where, why and how some fire
emergency happened.
In our solution, we use the integration of WSN and Radio Frequency
ID tags (RFIDs) to provide accurate localization reference and
other relevant contexts on the emergency on course.
Data from sensors and RFID tags at the location of the incident are
submitted to a fusion process to eliminate redundant data and
noise and so saving energy for the whole network.
The usage of mobile agents eliminates the need for all sensors to
send their readings back to a sink whenever some problem occurs.
In our solution the mobile agent, held by the sensors, and tailored
according to application needs (lowest latency, highest delivery
rate etc) is responsible for migrating, collecting the data and
performing data fusion at each step.
The novelty of our solution is the agents flexibility to
behavior and structure changes to guarantee the required quality
of service by the application when data is gathered and delivered
in harsh conditions.
http://www.ufscar.br
An Intelligent System Based on Cooperating Embedded Systems and
Wireless Sensors
Darkwolf
Networked Robotics

First stage of this project is to build a mobile robotic sensored
vehicle, capable of being controlled wirelessly, and via the agent
protocol, give status of the vehicle, as well as, serving, as
logging all movements, back to the agent server controller.
Next stage requires multiple vehicles to communicate with
each other, via agent protocols, and based on a given
algorithm, divide and conquer tasks in order to accomplish a
set goal (ie, such as best way to traverse a given course).
http://www.austincc.edu
MobiRouting
Intelligent Optical Network Management with Mobile Agent
E-Auction

This project foresees the enlargement of an existing single-source
surveillance system, developed at our lab, to a distributed
multi-camera video network.
Currently, the single-camera video system is applied for fall
detection in the so-called Video-Based Intelligent Home (ViBIH).
The main goal is thus to improve the accuracy of the fall detection
results and, at the same time, enhance the vision field.
Since we envision to use smart cameras, where the primary image
processing is performed close to the image sensor, the main
challenges faced by this project are: (i) the video sensor
units' connectivity, and (ii) the communication network.
As mentioned above, (i) comprises the process synchronization and
the cooperative integration of the multiple video productions.
It requires thus the definition of an appropriate data structure,
the development of the target algorithms for merging and
processing of the correlated info coming from different video sources,
as well as the prioritization of related tasks.
On the other hand, (ii) includes the definition of the communication
protocol and the memory management policy.
http://egyptnetwork.com
Intelligent Video Sensor Network - InViNe
Mobile-Agent-Based Autonomous Data Fusion for Distributed Sensors
Agent-Based Mobile Robot
Multi Agent Systems and Information Systems
TIPS: Transparent IP Sockets
Ambient Intelligence: a solution embedded and adaptive computing
Research and Development
Model of a mobile agent system for network administration
An agent-controlled system
Self-Healing Power Distribution Systems
Intrusion Detection using Mobile Agents
Mobile Agents in network Management
MAS for Data Center Energy Management
Agents to Manage Memory
RTS AI Development
Using Mobile-C to program a multi agent system
Tasks for multiagent enviroment using Artifical Intelligence
Mobile Agents for Computer Intrusion Detection
Mobile agent in DIS system
Optimisation of WSN using mobile agent
Study of the dynamics of the networks of sensors by the mobile agents
NEtwork Monitoring Infrastructure
VESTA
Virtual Guide for Students with Autism
Monitoring QoS on Telematic Devices
INTEGRA - Integrated Agricultural System for sustainable farming system

Traditional methods of farming and agriculture undergoes consistent change as
computational technology plays vital role in precision agriculture. The by-gone
methods of farming which involves time, space and cost, has been consistently
improved by various agricultural practices out of which precision agriculture
is currently on the up-surge.
INTEGRA (INTEgrated GRid framework for Agriculture ) discusses on methods to
built an effective farming system using wireless sensor networks built in
miniature Macronode. The system works on multiple crop growth concerned
parameters from seed to crop leading to utilization of available optimal
farming resources such that beneficial yeild can be achieved.
INTEGRA architecture works on multiple facets of computing techniques such as
Data Gathering methods, Data Aggregation, Mining Algorithms, and Event
monitoring, generation methods in order to achieve the expected output. INTEGRA
has been designed and implemented for two types of varying essential crops. The
system adapts to differing climatic needs and resources required to develop the
crop.
http://sites.google.com/site/integratedagricultureportal/
LMI

The LMI project is intended to explore the possibilities of contract based load response for power system operation and focuses on domestic and commercial demand as responsible loads.
The project follows some previous experiences of microgrid control by multi-agent systems as those shown at Joseba Jimeno, Jon Anduaga, José Oyarzabal and Asier Gil De Muro, "Architecture of a microgrid energy management system", Published online 26 April 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/etep.443
The LMI project is at its early stages but the agent platform could evolve from JADE to Mobile-C because of the difference in hardware requirements and suitability for embedded enviroments.
http://www.tecnalia.com/
|