Water management is paramount in countries with water scarcity. This also affects agriculture, as a large amount of water is dedicated to that use. The possible consequences of global warming lead to the consideration of creating water adaptation measures to ensure the availability of water for food production and consumption. Thus, studies aimed at saving water usage in the irrigation process have increased over the years. Typical commercial sensors for agriculture irrigation systems are very expensive, making it impossible for smaller farmers to implement this type of system. However, manufacturers are currently offering low-cost sensors that can be connected to nodes to implement affordable systems for irrigation management and agriculture monitoring. Due to the recent advances in IoT and WSN technologies that can be applied in the development of these systems, we present a survey aimed at summarizing the current state of the art regarding smart irrigation systems. We determine the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions. We provide an overview of the most utilized nodes and wireless technologies. Lastly, we will discuss the challenges and the best practices for the implementation of sensor-based irrigation systems.

Due to the growing interest using underwater acoustic networks, there are more and more research papers about underwater communications. These papers are mainly focused on deployments and studies about the constraints of the underwater medium. The underwater acoustic channel is highly variable and the signal transmission can change according to environmental factors, such as the temperature, pressure, or salinity of the water. For this reason, it is important to know how these devices are developed and the maximum distance and data transfer rates they can achieve. To this end, this paper presents an exhaustive study of existing underwater acoustic modems where their main features are highlighted. We also review the main features of their hardware. All presented proposals in the research literature are compared with commercial underwater acoustic modems. Finally, we analyze different programs and improvements of existing network simulators that are often used to simulate and estimate the behavior of underwater networks.

Advanced meter infrastructures (AMIs) are systems that measure, collect, and analyze utilities distribution and consumption, and communicate with metering devices either on a schedule or on request. AMIs are becoming a vital part of utilities distribution network and allow the development of Smart Cities. In this article we propose an integrated Internet of Things architecture for smart meter networks to be deployed in smart cities. We discuss the communication protocol, the data format, the data gathering procedure, and the decision system based on big data treatment. The architecture includes electricity, water, and gas smart meters. Real measurements show the benefits of the proposed IoT architecture for both the customers and the utilities.

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €.

Intelligent systems and communication technologies have experienced huge advances in the last few years. AAL can benefit from mixing both research fields. This article presents an intelligent communication architecture for AAL. It uses artificial intelligence to process the information gathered from several types of communication (e.g., wireless sensor networks, wireless ad hoc networks, wireless mesh networks) over any type of communication technologies (e.g., device-to-device, machine-to-machine, sensor-actuator), know what is happening in the network, and detect if elderly people need assistance. The article shows the main intelligent algorithms included in the AAL system and the developed software application. Several real measurements validate the operation of our proposal.

Deploying wireless sensor networks (WSN) in rural environments such as agricultural fields may present some challenges that affect the communication between the nodes due to the vegetation. These challenges must be addressed when implementing precision agriculture (PA) systems that monitor the fields and estimate irrigation requirements with the gathered data. In this paper, different WSN deployment configurations for a soil monitoring PA system are studied to identify the effects of the rural environment on the signal and to identify the key aspects to consider when designing a PA wireless network. The PA system is described, providing the architecture, the node design, and the algorithm that determines the irrigation requirements. The testbed includes different types of vegetation and on-ground, near-ground, and above-ground ESP32 Wi-Fi node placements. The results of the testbed show high variability in densely vegetated areas. These results are analyzed to determine the theoretical maximum coverage for acceptable signal quality for each of the studied configurations. The best coverage was obtained for the near-ground deployment. Lastly, the aspects of the rural environment and the deployment that affect the signal such as node height, crop type, foliage density, or the form of irrigation are discussed.