Electro-Quasistatic Human-Structure Coupling for Human Presence Detection and Secure Data Offloading.

The emergence of Human Body Communication (HBC), as an energy-efficient and physically secure mode of information exchange, has escalated the exploration of communication modalities between the human body and surrounding conducting objects. In this paper, we propose an Inter-Structure communication guided by Human Body while envisioning the need for non-contact sensing of biological objects such as humans with secure data offloading by analyzing the Structure-Human-Structure Interaction (SHSI) in Electro-Quasistatic (EQS) regime. Results show that the presence of a human between conducting structures (with Tx & Rx) can boost the received voltage by ~8 dB or more. Received signal level can be increased further by ~18 dB or more with a grounded receiver. Finite Element Method (FEM) based simulations are executed to study the positional variation of structure (with Rx) relative to body and earth's ground. Trends in simulation results are validated through experiments to develop an in-depth understanding of SHSI for EQS signals with low loss and enhanced physical security.

Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming.

Precision livestock farming (PLF) offers a strategic solution to enhance the management capacity of large animal groups, while simultaneously improving profitability, efficiency, and minimizing environmental impacts associated with livestock production systems. Additionally, PLF contributes to optimizing the ability to manage and monitor animal welfare while providing solutions to global grand challenges posed by the growing demand for animal products and ensuring global food security. By enabling a return to the "per animal" approach by harnessing technological advancements, PLF enables cost-effective, individualized care for animals through enhanced monitoring and control capabilities within complex farming systems. Meeting the nutritional requirements of a global population exponentially approaching ten billion people will likely require the density of animal proteins for decades to come. The development and application of digital technologies are critical to facilitate the responsible and sustainable intensification of livestock production over the next several decades to maximize the potential benefits of PLF. Real-time continuous monitoring of each animal is expected to enable more precise and accurate tracking and management of health and well-being. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring auditability in value chains while assuaging concerns associated with labor shortages. Despite notable advances in PLF technology adoption, a number of critical concerns currently limit the viability of these state-of-the-art technologies. The potential benefits of PLF for livestock management systems which are enabled by autonomous continuous monitoring and environmental control can be rapidly enhanced through an Internet of Things approach to monitoring and (where appropriate) closed-loop management. In this paper, we analyze the multilayered network of sensors, actuators, communication, networking, and analytics currently used in PLF, focusing on dairy farming as an illustrative example. We explore the current state-of-the-art, identify key shortcomings, and propose potential solutions to bridge the gap between technology and animal agriculture. Additionally, we examine the potential implications of advancements in communication, robotics, and artificial intelligence on the health, security, and welfare of animals.

Precision technologies are revolutionizing animal agriculture by enhancing the management of animal welfare and productivity. To fully realize the potential benefits of precision livestock farming (PLF), the development and application of digital technologies are needed to facilitate the responsible and sustainable intensification of livestock production over the next several decades. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring audibility in value chains while assuaging concerns associated with labor shortages. In this paper, we analyze the multilayered network of sensors, actuators, communication, and analytics currently in use in PLF. We analyze the various aspects of sensing, communication, networking, and intelligence on the farm leveraging dairy farms as an example system. We also discuss the potential implications of advancements in communication, robotics, and artificial intelligence on the security and welfare of animals.

Sub-GHz In-Body to Out-of-Body Communication Channel Modeling for Ruminant Animals for Smart Animal Agriculture.

Sensors in and around the environment becoming ubiquitous has ushered in the age of smart animal agriculture which has the potential to greatly improve animal health and productivity. The data gathered from sensors dwelling in animal agriculture settings have made farms a part of the IoT space leading to active research in developing efficient communication methodologies for farm networks. This study focuses on the first hop of farm networks where data from inside the body of animals is communicated to a node dwelling outside the body. Novel experimental methods are used to calculate the channel loss at sub-GHz frequencies (100-900 MHz) to characterize the in-body to out-of-body (IBOB) communication channel in large animals. A first-of-its-kind 3D bovine modeling is done with computer vision techniques for detailed morphological features of the animal body to perform Finite Element Method based Electromagnetic simulations. The results of the simulations are experimentally validated to build a complete channel modeling methodology for IBOB animal-body-communication. The 3D bovine model is made available publicly on GitHub. The results illustrate that an IBOB communication channel is realizable from the rumen to the collar of ruminants with [Formula: see text] path loss at sub-GHz frequencies making communication feasible. The developed methodology has been illustrated for ruminants but can also be used for other IBOB studies. An efficient communication architecture can be formed using the channel modeling technique illustrated for IBOB communication in animals paving the way for the design and development of future smart animal agriculture systems.

In-body to Out-of-body Communication Channel Modeling for Ruminant Animals for Smart Animal Agriculture.

Continuous real-time health monitoring in animals is essential for ensuring animal welfare. In ruminants like cows, rumen health is closely intertwined with overall animal health. Therefore, in-situ monitoring of rumen health is critical. However, this demands in-body to out-of-body communication of sensor data. In this paper, we devise a method of channel modeling for a cow using experiments and FEM based simulations at 400 MHz. This technique can be further employed across all frequencies to characterize the communication channel for the development of a channel architecture that efficiently exploits its properties.

Advanced Biophysical Model to Capture Channel Variability for EQS Capacitive HBC.

Human Body Communication (HBC) has come up as a promising alternative to traditional radio frequency (RF) Wireless Body Area Network (WBAN) technologies. This is essentially due to HBC providing a broadband communication channel with enhanced signal security in the physical layer due to lower radiation from the human body as compared to its RF counterparts. An in-depth understanding of the mechanism for the channel loss variability and associated biophysical model needs to be developed before electro-quasistatic (EQS) HBC can be used more frequently in WBAN consumer and medical applications. Recent developments have shown biophysical models that capture the channel response for fixed transmitter and receiver positions on the human body which do not capture the variability in the HBC channel for varying positions of the devices with respect to the body. In this study, we provide a detailed analysis of the change in path loss in a capacitive-HBC channel in the EQS domain. Causes of channel loss variability namely: inter-device coupling and effects of fringe fields due to body's shadowing effects are investigated. FEM based simulation results are used to analyze the channel response of human body for different positions and sizes of the device which are further verified using measurement results to validate the developed biophysical model. Using the biophysical model, we develop a closed form equation for the path loss in a capacitive HBC channel which is then analyzed as a function of the geometric properties of the device and the position with respect to the human body which will help pave the path towards future EQS-HBC WBAN design.