Nowadays, conventional agriculture farms lack high-level automated management due to the limited number of installed sensor nodes and measuring devices. Recent progress of the Internet of Things (IoT) technologies will play an essential role in future smart farming by enabling automated operations with minimum human intervention. The main objective of this work is to design and implement a flexible IoT-based platform for remote monitoring of agriculture farms of different scales, enabling continuous data collection from various IoT devices (sensors, actuators, meteorological masts, and drones). Such data will be available for end-users to improve decision-making and for training and validating advanced prediction algorithms. Unlike related works that concentrate on specific applications or evaluate technical aspects of specific layers of the IoT stack, this work considers a versatile approach and technical aspects at four layers: farm perception layer, sensors and actuators layer, communication layer, and application layer. The proposed solutions have been designed, implemented, and assessed for remote monitoring of plants, soil, and environmental conditions based on LoRaWAN technology. Results collected through both simulation and experimental validation show that the platform can be used to obtain valuable analytics of real-time monitoring that enable decisions and actions such as, for example, controlling the irrigation system or generating alarms. The contribution of this article relies on proposing a flexible hardware and software platform oriented on monitoring agriculture farms of different scales, based on LoRaWAN technology. Even though previous work can be found using similar technologies, they focus on specific applications or evaluate technical aspects of specific layers of the IoT stack.

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Internet of Things (IoT) technologies are opening new opportunities and services for different smart grid applications such as advanced meter infrastructures (AMI), distributed energy resources, and electric vehicles. Among these applications, AMIs represent the first step toward future smart grid implementation by enabling the reading and recording of electric power consumption on request or a schedule. In this study, the main focus is designing an IoT-based architecture to support AMIs' daily reporting and billing in a residential grid. First, the network modeling for AMI is discussed. Long range (LoRa) technology, as one of the promising candidates for long range low power wide area networks (LPWANs), has been studied and discussed. A comprehensive analysis of the LoRa-based architecture is given for a case study of an actual residential grid, Puerto Montt, Chile. The results are analyzed and discussed for packet delivery ratio, energy consumption, throughput, number of collisions, and frequency distribution.

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