RESUMEN
The Internet of Things (IoT) is playing a pivotal role in transforming various industries, and Wireless Sensor Networks (WSNs) are emerging as the key drivers of this innovation. This research explores the utilization of a heterogeneous network model to optimize the deployment of sensors in agricultural settings. The primary objective is to strategically position sensor nodes for efficient energy consumption, prolonged network lifetime, and dependable data transmission. The proposed strategy incorporates an offline model for placing sensor nodes within the target region, taking into account the coverage requirements and network connectivity. We propose a two-stage centralized control model that ensures cohesive decision making, grouping sensor nodes into protective boxes. This grouping facilitates shared resource utilization, including batteries and bandwidth, while minimizing box number for cost-effectiveness. Noteworthy contributions of this research encompass addressing connectivity and coverage challenges through an offline deployment model in the first stage, and resolving real-time adaptability concerns using an online energy optimization model in the second stage. Emphasis is placed on the energy efficiency, achieved through the sensor consolidation within boxes, minimizing data transmission hops, and considering energy expenditures in sensing, transmitting, and active/sleep modes. Our simulations on an agricultural farmland highlights its practicality, particularly focusing on the sensor placement for measuring soil temperature and humidity. Hardware tests validate the proposed model, incorporating parameters from the real-world implementation to enhance calculation accuracy. This study provides not only theoretical insights but also extends its relevance to smart farming practices, illustrating the potential of WSNs in revolutionizing sustainable agriculture.
RESUMEN
In this work, a fully optical Complementary Metal Oxide Semiconductor (CMOS) based catheter tracking system designed for 3 T Magnetic Resonance Imaging (MRI) environment is presented. The system aims to solve the Radio Frequency (RF) induced heating problem present in conventional wired catheter tracking systems used in MRI. It is based on an integrated circuit, consisting of a receiver and an optical power supply unit. The optical power supply unit includes a single on-chip photodiode and a DC-DC converter that boosts the low photodiode voltage output to voltages greater than 1.5 V. Through an optically driven switch, the accumulated charge on an a storage capacitor is transferred to the rest of the system. This operation is novel in the way that it is fully optical and the switch control is done through modulation of the applied light. An on-chip local oscillator signal for the receiver is avoided by application of an RF signal that is generated by the MRI machine at the receiving period. The signals received by a micro-coil antenna are processed by the on-chip direct conversion receiver. The processed signal is then transferred, also optically, to the outside world for tracking purposes. The frequency encoding method is used for MRI tracking. Operation with various levels of external optical power does not generate noticeble temperature increase in the system. The overall system is successfully tested in a 3 T MRI machine to demonstrate its full operation.
Asunto(s)
Imagen por Resonancia Magnética/instrumentación , Diseño de Equipo , Metales/química , Óxidos/química , Semiconductores , Relación Señal-RuidoRESUMEN
We describe a new method for frequency down-conversion of MR signals acquired with the radio-frequency projections method for device localization. A low-amplitude, off-center RF pulse applied simultaneously with the echo signal is utilized as the reference for frequency down-conversion. Because of the low-amplitude and large offset from the Larmor frequency, the RF pulse minimally interfered with magnetic resonance of protons. We conducted an experiment with the coil placed at different positions to verify this concept. The down-converted signal was transformed into optical signal and transmitted via fiber-optic cable to a receiver unit placed outside the scanner room. The position of the coil could then be determined by the frequency analysis of this down-converted signal and superimposed on previously acquired MR images for comparison. Because of minimal positional errors (≤ 0.8 mm), this new device localization method may be adequate for most interventional MRI applications.