PEACH: predicting frost events in peach orchards using IoT technology

In 2013, 85% of the peach production in the Mendoza region (Argentina) was lost because of frost. In a couple of hours, farmers can lose everything. Handling a frost event is possible, but it is hard to predict when it is going to happen. The goal of the PEACH project is to predict frost events by analyzing measurements from sensors deployed around an orchard. This article provides an in-depth description of a complete solution we designed and deployed: the low-power wireless network and the back-end system. The low-power wireless network is composed entirely of commercial off-the-shelf devices. We develop a methodology for deploying the network and present the open-source tools to assist with the deployment and to monitor the network. The deployed low-power wireless mesh network is 100% reliable, with end-to-end latency below 2 s, and over 3 years of battery lifetime. This article discusses how the technology used is the right one for precision agriculture applications.EEA JunínFil: Watteyne, Thomas. Institut National de Recherche en Informatique et en Automatique (INRIA). EVA Team; FranciaFil: Diedrichs, Ana Laura. Universidad Tecnológica Nacional (UTN), Mendoza; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Brun-Laguna, Keoma. Institut National de Recherche en Informatique et en Automatique (INRIA). EVA Team; FranciaFil: Chaar, Javier Emilio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Junín; ArgentinaFil: Dujovne, Diego. Universidad Diego Portales (UDP), Santiago; ChileFil: Taffernaberry, Juan Carlos. Universidad Tecnológica Nacional (UTN), Mendoza; ArgentinaFil: Mercado, Gustavo. Universidad Tecnológica Nacional (UTN), Mendoza; Argentin

SmartMesh IP Network and IoT System

In recent years, a great deal of research conducted in a variety of scientific areas, including physics, microelectronics, and material science, by scientific experts from different domains of expertise has resulted in the invention of Micro-Electro-Mechanical Systems (MEMS). As MEMS became very popular and widely used, the need for combining the capabilities of sensing, actuation, processing, and communication also grew, and led to further research which would result in the design and implementation of devices which could reflect all those four capabilities. These devices became knowns as Wireless Sensor Networks (WSNs) and they have been the focus of considerable research efforts in the areas of communications (routing, coding, error detection, error correction, and protocols), electronics (miniaturization and energy efficiency), and control (networked control system, theory, and applications). SmartMesh IP is an innovative way to connect WSNs with advanced network management and comprehensive security features. It follows the IEEE 802.15.4e Timeslotted Channel Hopping (TSCH) standard. SmartMesh IP delivers reliable, scalable, and energy efficient wireless sensor connectivity. Using up to eight times less power than other solutions, SmartMesh IP has become the industry’s most energy-efficient wireless mesh sensing technology even in harsh and dynamically changing RF environments. Therefore, it is an excellent way to create a smart low-power network infrastructure. Thus, the main objectives of this work are: 1) designing and developing a SmartMesh IP system for teaching and research purposes at St. Cloud State University, 2) developing lab procedures for two senior elective classes at St. Cloud State University. The lab procedures are for network manager and mote configuration, and operation control of the embedded system on the mote. 3) testing the performance of SmartMesh IP systems with several configurations. To accomplish the above objectives, here are the tasks that I have completed: 1) Study of the SmartMesh IP Design: Performed extensive study of SmartMesh IP design resources including documentations and source codes. 2) Design of a SmartMesh IP Configuration software: this software has been designed and developed for configuring SmartMesh IP network managers, motes, and access points. 3) Design of a SmartMesh IP Temperature Logger software: this software has been designed and developed for monitoring the temperature data collected within a SmartMesh IP network using motes’ internal temperature sensors. 4) Design of a SmartMesh IP Network Statistics software: this software has been designed and developed for monitoring the statistics data (such as reliability, stability, and latency statistics) collected within a SmartMesh IP network. 5) Design of a SmartMesh IP Network Topology software: this software has been designed and developed for viewing the topology layout of a SmartMesh IP network. 6) Design of SmartMesh IP Temperature Plotter firmware and software: this platform has been designed and developed for monitoring the temperature data from external temperature sensors through ADC processing. 7) Design of SmartMesh IP Oscilloscope firmware and software: this platform has been designed and developed for viewing an analog signal’s digitized data. To complete the above tasks, I relied heavily on the resources found in the dustcloud Community SmartMesh IP website: https://dustcloud.atlassian.net/wiki/spaces/ALLDOC/overview In the end, a SmartMesh IP network and IoT system was successfully designed and developed. Also, the system was tested with 100% reliability under several applications and configurations

A Demo of the PEACH IoT-based Frost Event Prediction System for Precision Agriculture

International audienceIn 2013, 85% of the peach production in the Mendoza region (Argentina) was lost because of frost. In a couple of hours, farmers can lose everything. Handling a frost event is possible, but it is hard to predict when it is going to happen. The goal of the PEACH project is to predict frost events by analyzing measurements from sensors deployed around an orchard. This demo provides an overview of the complete solution we designed and deployed: the low-power wireless network and the back-end system. The low-power wireless network is composed entirely of commercial off-the-shelf devices. We develop a methodology for deploying the network and present the open-source tools to assist with the deployment, and to monitor the network. The deployed low-power wireless mesh network, built around SmartMesh IP, is 100% reliable, with end-to-end latency below 2 s, and over 3 years of battery lifetime

Long-term Monitoring of the Sierra Nevada Snowpack Using Wireless Sensor Networks

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Application of Big Data Analysis to Agricultural Production, Agricultural Product Marketing, and Influencing Factors in Intelligent Agriculture

Agricultural Internet of things (AIoT) promotes the modernization of traditional agricultural production and marketing model. However, the existing time series prediction methods for agricultural production and agricultural product (AP) marketing cannot adapt well to most real-world scenarios, failing to realize multistep forecast of production and AP marketing data. To solve the problem, this paper explores the big data analysis of agricultural production, AP marketing, and influencing factors in intelligent agriculture. To realize long-, and short-term predictions, a small-sample time series model was set up for AIoT production, and a big-sample time series model was constructed for AP marketing. The data fusion algorithm based on Kalman filter (KF) was adopted to fuse the massive multi-source AP marketing data. The proposed strategy was proved valid through experiments

A Historical Twist on Long-Range Wireless: Building a 103 km Multi-Hop Network Replicating Claude Chappe's Telegraph

International audienceIn 1794, French Engineer Claude Chappe coordinated the deployment of a network of dozens of optical semaphores. These formed “strings” that were hundreds of kilometers long, allowing for nationwide telegraphy. The Chappe telegraph inspired future developments of long-range telecommunications using electrical telegraphs and, later, digital telecommunication. Long-range wireless networks are used today for the Internet of Things (IoT), including industrial, agricultural, and urban applications. The long-range radio technology used today offers approximately 10 km of range. Long-range IoT solutions use “star” topology: all devices need to be within range of a gateway device. This limits the area covered by one such network to roughly a disk of a 10 km radius. In this article, we demonstrate a 103 km low-power wireless multi-hop network by combining long-range IoT radio technology with Claude Chappe’s vision. We placed 11 battery-powered devices at the former locations of the Chappe telegraph towers, hanging under helium balloons. We ran a proprietary protocol stack on these devices so they formed a 10-hop multi-hop network: devices forwarded the frames from the “previous” device in the chain. This is, to our knowledge, the longest low power multi-hop wireless network built to date, demonstrating the potential of combining long-range radio technology with multi-hop technology

Initial Design of a Generalization of the 6TiSCH Standard to Support Multiple PHY Layers

This report introduces early results from an experiment to integrate multiple radios in the same 6TiSCH network. It is provides an initial step towards the publication of an article tentatively titled “Generalized 6TiSCH for an Agile Multi-PHY Wireless Networking”. The work discussed the architecture of the proposed solution, and presents its performance compared to single-PHY networks.Ce rapport contient des résultats préliminaires d’une étude pour utiliser plusieurs couches physiques dans un même réseau 6TiSCH. Il s’agit d’une première étape dans le but de publier nos travaux complets, sous le titre (en anglais) “Generalized 6TiSCH for an Agile Multi-PHY Wireless Networking”. Ce rapport détaille l’architecture évaluée, et présente les performance de l’approche, en comparaison avec un réseau qui n’utilise qu’une seule couche physique

Wireless Technologies for Industry 4.0 Applications

Wireless technologies are increasingly used in industrial applications. These technologies reduce cabling, which is costly and troublesome, and introduce several benefits for their application in terms of flexibility to modify the layout of the nodes and scaling of the number of connected devices. They may also introduce new functionalities since they ease the connections to mobile devices or parts. Although they have some drawbacks, they are increasingly accepted in industrial applications, especially for monitoring and supervision tasks. Recently, they are starting to be accepted even for time-critical tasks, for example, in closed-loop control systems involving slow dynamic processes. However, wireless technologies have been evolving very quickly during the last few years, since several relevant technologies are available in the market. For this reason, it may become difficult to select the best alternative. This perspective article intends to guide application designers to choose the most appropriate technology in each case. For this purpose, this article discusses the most relevant wireless technologies in the industry and shows different examples of applications