Agriculture has a significant role in countries' economy, but irrigation process consumes both power and water resources. Since in agriculture the goal is to maximize crop's yields with minimize costs, it is important to design a national smart irrigation system with optimal allocation of power and water resources especially in a plantation area with little rains. In this work, an optimized on-demand smart irrigation system is proposed to manage the allocation of the consumed power and water in agriculture field. The system controls irrigation process by utilizing Wireless Sensor Network (WSN) to collect real-time data from the field using sensors. Raspberry pi takes appropriate decision about irrigation process according to received data from sensor nodes, and commands are sent from it to actuator nodes. Secured Message Queuing Telemetry Transport (MQTT) protocol with Transport Layer Security (TLS) authentication protocol is used in managing the data exchange in the network over Wi-Fi technology. In addition, an optimal power and water consumptions formula is derived using Lagrange Multiplier method to allocate resources in an optimal way depending on watering demands. Both theoretical and practical results approve the efficiency of the proposed system in managing irrigation process optimally.
<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant maximization in the communication cost, which boosts the total energy depletion. This paper proposes a lightweight routes re-adjustment strategy for mobile sink wireless sensor networks (LRAS-MS) aimed at minimizing communication cost and energy consumption by reducing route re-adjustment in a cluster-based WSN environment. The simulation results show a significant reduction in communication costs and extending the network lifetime while maintaining comparable low data delivery delay. </span>
It is well known that the resources in agriculture are considered the most important factors for success. Therefore, numerous researchers are involved in the field of managing these resources, particularly water and consumed power. Moreover, the security side of these resources is considered, particularly the cyber-attacks. In this project, an optimized resource management method is proposed for allocating the available resources in a smart on-demand way. The proposed method is applied for dripped and sprinkler irrigation systems for managing the available water and generated power. In addition, an optimization method is utilized to obtain reliable solutions for managing the adopted resources. This method adopts a cyber security algorithm for preventing any possible attack. Wireless sensor network (WSN) is used as a reading source, in which the underlying area is covered well, since using sensors in irrigation systems is cost-effective that ensures on-demand irrigation process to save water and power resources. This network is supported by the fault tolerance method to increase availability.
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