The Design and Deployment of an End-To-End IoT Infrastructure for the Natural Environment

Abstract

Internet of Things (IoT) systems have seen recent growth in popularity for city and home environments. We report on the design, deployment, and use of the IoT infrastructure for environmental monitoring and management. Working closely with hydrologists, soil scientists, and animal behaviour scientists, we successfully deployed and utilised a system to deliver integrated information across these two fields in the first such example of real-time multidimensional environmental science. We describe the design of this system; its requirements and operational effectiveness for hydrological, soil, and ethological scientists; and our experiences from building, maintaining, and using the deployment at a remote site in difficult conditions. Based on this experience, we discuss key future work for the IoT community when working in these kinds of environmental deployments.

Wireless Sensor Network Synchronization for Precision Agriculture Applications

“…Due to their high customization capabilities, a popular WSN configuration, uses Arduino sensors [56] to generate environmental measurements and utilizes the ZigBee module for communication purposes, as described by Satyanarayana and Mazaruddin [57] and Papamichail et al [58], whilst extensively documented by Kooijman [59]. However, with the coming of IoT, more microcontrollers have come to light in order to support or even remotely control the Arduino processes, such as Raspberry Pis [60,61], which can be setup to act as sensors [62], gateways [63], databases [64], servers [65] or fog devices [66].…”

“…The abundance of such devices has triggered new methods that provide increased land coverage, reliable transmissions, flexibility and scalability, even under harsh environmental conditions. For example, the authors of [63] reported the design and development of an end-to-end system in Northern Wales comprising Arduino sensors and incorporating Raspberry Pis, used as gateways for interconnection with a cloud server.…”

Research on Cooperative Communication Strategy and Intelligent Agent Directional Source Grouping Algorithms for Internet of Things

“…A multi-mobile agent travel planning algorithm (CL-MIP) is proposed in the literature [7]. It divides the problem of multi-mobile agent WSNs into four steps: (1) calculating the density center of the source node in the network; (2) taking the density center as the center of circle, with the predefined radius, the source nodes that are covered are grouped into one group; (3) computing the order in which each mobile agent accesses the source nodes in the group; (4) continuing to iterate until there is no unmarshalled node in the network, and sending multiple mobile agent packets in parallel. A system structure for the research of multi-mobile agent travel planning is provided by CL-MIP.…”

“…The following problems are presented in single agent data. 1 Larger latency: when a single agent needs to access hundreds of nodes. 2 Load imbalance: the use of a single agent results in two kinds of energy consumption imbalance.…”

“…In recent years, wireless sensor networks (WSNs) are an important part of the Internet of Things (IoT). They have undergone tremendous development [1]. The wireless channel of WSN in the The remainder of the paper is structured as follows.…”