LoRaWAN device security and energy optimization

Resource-constrained devices are commonly connected to a network and become things that make up the Internet of Things (IoT). Many industries are interested in cost-effective, reliable, and cyber secure sensor networks due to the ever-increasing connectivity and benefits of IoT devices. The full advantages of IoT devices are seen in a long-range and remote context. However, current IoT platforms show many obstacles to achieve a balance between power efficiency and cybersecurity. Battery-powered sensor nodes can reliably send data over long distances with minimal power draw by adopting Long-Range (LoRa) wireless radio frequency technology. With LoRa, these devices can stay active for many years due to a low data bit rate and low power draw during device sleep states. An improvement built on top of LoRa wireless technology, Long-Range Wide Area Networks (LoRaWAN), introduces integrity and confidentiality of the data sent within the IoT network. Although data sent from a LoRaWAN device is encrypted, protocol and implementation vulnerabilities still exist within the network, resulting in security risks to the whole system. In this research, solutions to these vulnerabilities are proposed and implemented on a LoRaWAN testbed environment that contains devices, gateways, and servers. Configurations that involve the transmission of data using AES Round Reduction, Join Scheduling, and Metadata Hiding are proposed in this work. A power consumption analysis is performed on the implemented configurations, resulting in a LoRaWAN system that balances cybersecurity and battery life. The resulting configurations may be harnessed for usage in the safe, secure, and efficient provisioning of LoRaWAN devices in technologies such as Smart-Industry, Smart-Environment, Smart-Agriculture, Smart-Universities, Smart-Cities, et

Internet of things and LoRaWAN enabled future smart farming

It is estimated that to keep pace with the predicted population growth over the next decades, agricultural processes involving food production will have to increase their output up to 70 percent by 2050. "Precision" or "smart" agriculture is one way to make sure that these goals for future food supply, stability, and sustainability can be met. Applications such as smart irrigation systems can utilize water more efficiently, optimizing electricity consumption and costs of labor; sensors on plants and soil can optimize the delivery of nutrients and increase yields. To make all this smart farming technology viable, it is important for it to be low-cost and farmer-friendly. Fundamental to this IoT revolution is thus the adoption of low-cost, long-range communication technologies that can easily deal with a large number of connected sensing devices without consuming excessive power. In this article, a review and analysis of currently available long-range wide area network (LoRaWAN)-enabled IoT application for smart agriculture is presented. LoRaWAN limitations and bottlenecks are discussed with particular focus on their effects on agri-tech applications. A brief description of a testbed in development is also given, alongside a review of the future research challenges that this will help to tackle

Development and Characterization of an IoT Network for Agricultural Imaging Applications

Smart agriculture is an increasingly popular field in which the technology of wireless sensor networks (WSN) has played a large role. Significant research has been done at Cal Poly and elsewhere to develop a computer vision (CV) and machine learning (ML) pipeline to monitor crops and accurately predict crop yield numbers. By autonomously providing farmers with this data, both time and money are saved. During the past development of a prediction pipeline, the primary focuses were CV and ML processing while a lack of attention was given to the collection of quality image data. This lack of focus in previous research presented itself as incomplete and inefficient processing models. This thesis work attempts to solve this image acquisition problem through the initial development and design of an Internet of Things (IoT) prototype network to collect consistent image data with no human interaction. The system is developed with the goals of being low-power, low-cost, autonomous, and scalable. The proposed IoT network nodes are based on the ESP32 SoC and communicate over-the-air with the gateway node via Bluetooth Low Energy (BLE). In addition to BLE, the gateway node periodically uplinks image data via Wi-Fi to a cloud server to ensure the accessibility of collected data. This research develops all functionality of the network, comprehensively characterizes the power consumption of IoT nodes, and provides battery life estimates for sensor nodes. The sensor node developed consumes a peak current of 150mA in its active state and sleeps at 162µA in its standby state. Node-to-node BLE data transmission throughput of 220kbps and node-tocloud Wi-Fi data transmission throughput of 709.5kbps is achieved. Sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day. This network can be utilized by any application that requires a wireless sensor network (WSN), high data rates, low power consumption, short range communication, and large amounts of data to be transmitted at low frequency intervals

Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth