The main challenges in modern agriculture involve addressing the disruptive environmental effects caused by crop and livestock production, which are essential for human survival. Emerging trends point towards a world of pervasive IoT (Internet of Things) nodes, where low-cost, low-power, and in-vivo plant sensors can detect abiotic and biotic stresses at the earliest stages. This paper presents a preliminary study of an integrable, low-power relaxation oscillator, consisting of a Schmitt trigger in a feedback loop with the plant’s stem to evaluate its health status. Simulations have been conducted to compare the energy consumption of this circuit with state-of-the-art electronic sensors, focusing on energy usage per measurement. The results indicate that this new solution can sense the plant’s health status with an energy consumption below 10 µJ per measurement, which is at least an order of magnitude lower than existing electronic systems found in the literature.

Food production is one of the main contributors to climate change and its impact is set to increase due to population growth. Smart agriculture aims at providing solutions to reduce food production and environmental impact while, at the same time, increasing crop production. This paper proposes a system based on STDES-BTAG01 by STMicroelectronics to monitor in-vivo stem electrical impedance, which is a parameter that has recently demonstrated its efficacy in assessing information about plants' water stress status. The developed system is completely battery-free and equipped with a wireless communication module to transmit the acquired data. It is powered by a small amorphous solar cell and transmits data to a base station exploiting the Bluetooth Low Energy (BLE) protocol. The system monitors the needed time to discharge a capacitor through the plant stem. After this, this span of time is used to compute the stem electrical impedance. Tests showed reading errors lower than 15% when dealing with impedance modules up to 180 kΩ. System characteristics (energy self-sufficiency, compactness, and low-power consumption) make the system implementable in the fields.

Molecular Field-Coupling Nanocomputing (FCN) is one of the most promising technologies for overcoming Complementary Metal Oxide Semiconductor (CMOS) scaling issues. It encodes the information in the charge distribution of nanometric molecules and propagates it through local electrostatic intermolecular interaction. This technology promises very high speed at ambient temperatures with minimal power dissipation. The main research focus on molecular FCN is currently either on single-molecule low-level analysis or circuit design based on naïve assumptions. We aim to fill this gap, assessing the potential and feasibility of FCN. We present a bottom-up analysis and design framework that starts from the physical characterization of molecular and technological parameters and enables physical-aware FCN designs. The framework explicitly considers molecular physics, allowing the designer to tame the molecular interaction to ensure the computational capabilities of the final device. The framework permits studying possible physical effects that create cross-implications and correlations among physical and system-level layers considering possible behavior variability. We characterize and verify molecular propagation in increasingly structured layouts to design complex arithmetic circuits. The results highlight molecular FCN advantages, especially in area occupation, and provide valuable quantitative feedback to designers and technologists to support the assessment of molecular FCN and the realization of an eventual prototype.

World population growth and desertification are the most severe issue to agricultural food production. Smart agriculture is a promising solution to ensure food security. The use of sensors to monitor crop production can help farmers improve the yield and reduce water consumption. Here we propose a study where the electrical impedance of green plants' stem is analyzed in vivo, along with environmental conditions. In particular, the variations associated with the daily cycle are highlighted. These analyses lead to the possibility of understanding plant status directly from stem impedance.

Many beyond-CMOS technologies, based on different switching mechanisms, are arising. Field-coupled technologies are the most promising as they can guarantee an extremely low-power consumption and combine logic and memory into the same device. However, circuit-level explorations, like layout verification and analysis of the circuit performance, considering the constraints of the target technology, cannot be done using existing tools. Here, we propose a methodology to take on this challenge. We present function and connection detection (FUNCODE), an algorithm that can detect element connections, functions, and errors of custom layouts and generate its corresponding very high-speed integrated circuits hardware description language netlist. It is proposed for in-plane and perpendicular nanomagnetic logic as a case study. FUNCODE netlists, which take into account the physical behavior of the technology, were verified using circuits with increasing complexity, from 6 up to 1400 gates with a number of layout elements varying from 200 to 2.3e6.

Field-coupled Nanocomputing (FCN) is a computing concept with several promising post-CMOS candidate implementations that offer tremendously low power dissipation and highest processing performance at the same time. Two of the manifold physical implementations are Quantum-dot Cellular Automata (QCA) and Nanomagnet Logic (NML). Both inherently come with domain-specific properties and design constraints that render established conventional design algorithms inapplicable. Accordingly, dedicated design tools for those technologies are required. This paper provides an overview of two leading examples of such tools, namely fiction and ToPoliNano. Both tools provide effective methods that cover aspects such as placement, routing, clocking, design rule checking, verification, and logical as well as physical simulation. By this, both freely available tools provide platforms for future research in the FCN domain.

With the growth of world population and food demand, it is crucial to optimize water consumption for agriculture cultivation. Here we propose a method to monitor plant status, relating the measured parameters to the watering or drying situation of a single plant. Plant trunk electrical impedance measurements and environmental parameters were analyzed with a statistical approach. Correlation and causality among the data are showed and analyzed. In this way, it was possible to easily obtain the needed information about plant status.