25 research outputs found
Solar-powered aquaponics prototype as sustainable approach for food production
This paper presents the establishment of a solar-powered aquaponics prototype as a sustainable, cost
effective and environmentally sound approach for food production. In this study, a prototype bench
top aquaponics rig with an integrated 20 W solar panel were fabricated for the cultivation of red
Hybrid Tilapia (Oreochromis spp.) and leaf mustard (Brassica juncea). The size of the fish tank is about
29.5L and serves as the base for the setup. Additionally, the hydroponic grower compartment (0.45 m
(L) � 0.32 m (W) � 0.13 m (H)) was stacked on top of the fish tank and was filled with LECA media
bed for the plant growth. Two important operating parameters were studied. First, the amount of energy
produced by the solar panel and the energy consumption by the water pump used in the setup. Secondly,
the resultant effects from fish cultivation and plants growth on the water qualities and nitrification effi�ciency of the aquaponics unit. The aquaponics unit was operated for a month and the values of pH, tem�perature, and ammonia level were measured to be within the range of 6.4–7.2, 27.1–31.7 �C, and
1 mg�L�1
, respectively. Survival rate for fish was about 75% with specific growth rate (SGR) of 3.75%
per day and food conversion ratio of about 1.15. A slight nutrient deficiency was evident and plants
showed a healthy growth with height gain as high as 5 cm was achieved. Despite raining season, our data
shows that the energy produced via 20 W solar panel enabled the unit to run at night without depending
on local electricity for nearly two hours. Clearly, a larger solar panel is needed for longer operation.
Nevertheless, the study has proven the potential of operating a low cost aquaponics setup using renew�able energy for a sustainable food production method
Task Allocation of Wasps Governed by Common Stomach: A Model Based on Electric Circuits
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Simple regulatory mechanisms based on the idea of the saturable common stomach\u27 can control the regulation of construction behavior and colony-level responses to environmental perturbations in Metapolybia wasp societies. We mapped the different task groups to mutual inductance electrical circuits and used Kirchoff\u27s basic voltage laws to build a model that uses master equations from physics, yet is able to provide strong predictions for this complex biological phenomenon. Similar to real colonies, independently of the initial conditions, the system shortly sets into an equilibrium, which provides optimal task allocation for a steady construction, depending on the influx of accessible water. The system is very flexible and in the case of perturbations, it reallocates its workforce and adapts to the new situation with different equilibrium levels. Similar to the finding of field studies, decreasing any task groups caused decrease of construction; increasing or decreasing water inflow stimulated or reduced the work of other task groups while triggering compensatory behavior in water foragers. We also showed that only well connected circuits are able to produce adequate construction and this agrees with the finding that this type of task partitioning only exists in larger colonies. Studying the buffer properties of the common stomach and its effect on the foragers revealed that it provides stronger negative feedback to the water foragers, while the connection between the pulp foragers and the common stomach has a strong fixedpoint attractor, as evidenced by the dissipative trajectory
UAV-CLOUD: A PLATFORM FOR UAV RESOURCES AND SERVICES ON THE CLOUD
UAVs - Unmanned Aerial Vehicles – have gained significant attention recently, due to the increasingly growing range of applications. However, developing collaborative UAV applications using traditional technologies in a tightly coupled design requires a great deal of development effort, time, and budget especially for heterogeneous UAVs. Moreover, monitoring and accessing UAV resources using traditional communication media suffer from several restrictions and limitations. This research aims to simplify the efforts, reduce the time, and lower the costs of developing collaborative applications for distributed heterogeneous UAVs. In addition, the research aims to provide ubiquitous UAV resources access. A platform is proposed for developing distributed UAVs. This platform provides services to simplify application development. In this approach, UAVs are integrated with the Cloud Computing paradigm to provide ubiquitous access to their resources and services. Due to the limited capabilities of UAVs, a lightweight architecture is adopted. UAV resources and services are modeled in a Resource Oriented Architecture which is a new flexible web service design pattern with loosely coupled interaction between services. Hence, they are accessed as Representational State Transfer RESTful services using HTTP. Moreover, the research proposes using a broker architecture to increase efficiency by separating responsibilities. Therefore, it separates the requester’s logic and functionalities from the provider’s. It also takes the responsibility for allocating the issued request to the available and suitable UAV(s). To test the proposed platform, I first developed the UAV resources as a payload subsystem then provided them with Internet connectivity. Then, resource identifiers and uniform interfaces were developed using the RESTful Application Programming Interfaces (APIs). I also developed the broker service along with a database containing the information of the registered UAVs and their resources. The platform system components were tested using a requester interface in a browser by issuing a request for a resource to the broker to find and request the service from a suitable UAV. The test was done for retrieving data from UAVs as well as requesting actions from them. The main contributions of this research are proposing the UAV-Cloud platform for simplifying the development of ubiquitous UAV applications and its vii perspectives, as well as a lightweight loosely coupled design for UAV resources. Another contribution is developing the broker architecture for separating responsibilities in this platform
Auction-based Charging Scheduling with Deep Learning Framework for Multi-Drone Networks
State-of-the-art drone technologies have severe flight time limitations due
to weight constraints, which inevitably lead to a relatively small amount of
available energy. Therefore, frequent battery replacement or recharging is
necessary in applications such as delivery, exploration, or support to the
wireless infrastructure. Mobile charging stations (i.e., mobile stations with
charging equipment) for outdoor ad-hoc battery charging is one of the feasible
solutions to address this issue. However, the ability of these platforms to
charge the drones is limited in terms of the number and charging time. This
paper designs an auction-based mechanism to control the charging schedule in
multi-drone setting. In this paper, charging time slots are auctioned, and
their assignment is determined by a bidding process. The main challenge in
developing this framework is the lack of prior knowledge on the distribution of
the number of drones participating in the auction. Based on optimal
second-price-auction, the proposed formulation, then, relies on deep learning
algorithms to learn such distribution online. Numerical results from extensive
simulations show that the proposed deep learning-based approach provides
effective battery charging control in multi-drone scenarios.Comment: 14 pages, 19 figures, IEEE Transactions on Vehicular Technology (
Volume: 68 , Issue: 5 , May 2019
Emergent Task Allocation for Mobile Robots through Intentions and Directives
Multi-robot systems require efficient and accurate planning in order to perform mission-critical tasks. However, algorithms that find the optimal solution are usually computationally expensive and may require a large number of messages between the robots as the robots need to be aware of the global spatiotemporal information. In this paper, we introduce an emergent task allocation approach for mobile robots. Each robot uses only the information obtained from its immediate neighbors in its decision. Our technique is general enough to be applicable to any task allocation scheme as long as a utilization criteria is given. We demonstrate that our approach performs similar to the integer linear programming technique which finds the global optimal solution at the fraction of its cost. The tasks we are interested in are detecting and controlling multiple regions of interest in an unknown environment in the presence of obstacles and intrinsic constraints. The objective function contains four basic requirements of a multi-robot system serving this purpose: control regions of interest, provide communication between robots, control maximum area and detect regions of interest. Our solution determines optimal locations of the robots to maximize the objective function for small problem instances while efficiently satisfying some constraints such as avoiding obstacles and staying within the speed capabilities of the robots, and finds an approximation to global optimal solution by correlating solutions of small problems
Aerial Remote Sensing in Agriculture: A Practical Approach to Area Coverage and Path Planning for Fleets of Mini Aerial Robots
In this paper, a system that allows applying precision agriculture techniques is described. The application is based on the deployment of a team of unmanned aerial vehicles that are able to take georeferenced pictures in order to create a full map by applying mosaicking procedures for postprocessing. The main contribution of this work is practical experimentation with an integrated tool. Contributions in different fields are also reported. Among them is a new one-phase automatic task partitioning manager, which is based on negotiation among the aerial vehicles, considering their state and capabilities. Once the individual tasks are assigned, an optimal path planning algorithm is in charge of determining the best path for each vehicle to follow. Also, a robust flight control based on the use of a control law that improves the maneuverability of the quadrotors has been designed. A set of field tests was performed in order to analyze all the capabilities of the system, from task negotiations to final performance. These experiments also allowed testing control robustness under different weather conditions
Contextual and Possibilistic Reasoning for Coalition Formation
In multiagent systems, agents often have to rely on other agents to reach
their goals, for example when they lack a needed resource or do not have the
capability to perform a required action. Agents therefore need to cooperate.
Then, some of the questions raised are: Which agent(s) to cooperate with? What
are the potential coalitions in which agents can achieve their goals? As the
number of possibilities is potentially quite large, how to automate the
process? And then, how to select the most appropriate coalition, taking into
account the uncertainty in the agents' abilities to carry out certain tasks? In
this article, we address the question of how to find and evaluate coalitions
among agents in multiagent systems using MCS tools, while taking into
consideration the uncertainty around the agents' actions. Our methodology is
the following: We first compute the solution space for the formation of
coalitions using a contextual reasoning approach. Second, we model agents as
contexts in Multi-Context Systems (MCS), and dependence relations among agents
seeking to achieve their goals, as bridge rules. Third, we systematically
compute all potential coalitions using algorithms for MCS equilibria, and given
a set of functional and non-functional requirements, we propose ways to select
the best solutions. Finally, in order to handle the uncertainty in the agents'
actions, we extend our approach with features of possibilistic reasoning. We
illustrate our approach with an example from robotics