Search Results (79)

The paper presents a low-cost agricultural monitoring platform based on embedded IoT sensing, LoRa mesh communication, and an Edge–Fog–Cloud architecture designed for real-time environmental monitoring in smart agriculture applications. The proposed system integrates distributed sensor nodes built around the Heltec Mesh Node T114 platform, combining an nRF52840 microcontroller with an SX1262 LoRa transceiver to support low-power, long-range communication in agricultural environments. Environmental data acquisition is performed using integrated BME280 temperature, humidity, and pressure sensors, capacitive soil moisture sensors, and TEMT6000 light sensors. A custom firmware architecture extending the Meshtastic framework was developed to support sensor integration, telemetry generation, packet forwarding, and energy-aware scheduling within the LoRa mesh network. The platform combines embedded telemetry modules, intermediate routing mechanisms, and cloud-based microservices responsible for data aggregation and processing. Experimental results showed stable radio-link conditions in the tested node-to-router configuration, with RSSI values around −55 dBm and SNR values of approximately 6–7 dB. Channel utilization varied between approximately 4% and 12%, while transmission airtime utilization remained below 5%. These results support the feasibility of the proposed sensing, communication, and data-processing architecture under the tested configuration. The architecture is designed to accommodate additional sensing and routing nodes, while multi-hop performance, long-term energy consumption, and network scalability remain to be evaluated in larger deployments. Full article

The rapid proliferation of Internet of Things (IoT) technologies and smart grids has substantially intensified the cybersecurity challenges associated with smart energy meters (SEMs). The data collected by the plugs are transmitted via a wireless communication protocol to a smart electricity meter that acts as a local gateway. This meter centralizes the information from the various sensors, may perform data pre-processing, aggregation, or validation operations, and then forwards the information to a central server. The main contributions of this system can be categorized into two key aspects. First, the implementation of a centralized wireless local energy consumption network using the Wi-Fi protocol to coordinate smart plugs over distances of up to 20 m. Second, the real-time acquisition of power characteristics and the remote control (ON/OFF switching) of household appliances for direct appliance-level submetering purposes. Data collected by the smart meter are transmitted to a processing unit through a Semtech SX1276 LoRa transceiver communication link. The central server constitutes the processing and storage layer of the system: it receives the collected data, archives it in a dedicated database, and makes it available through analysis, visualization, and decision-support tools. This architecture enables real-time monitoring of energy consumption, anomaly detection, optimization of electrical resource use, and the development of effective energy management strategies for smart electrical grids. Although current smart meter architectures incorporate multi-layer protection mechanisms at the hardware, communication, and data levels, additional security measures are required to counter advanced cyber threats aimed at data interception and manipulation. This paper improves the security framework of smart energy meters by integrating a chaos-based encryption layer to ensure secure data transmission. Chaotic systems exhibit intrinsic properties such as sensitivity to initial conditions, pseudo-randomness, and ergodicity, which render them particularly suitable for cryptographic applications. The proposed framework employs a Lorenz-based chaotic encryption module to secure SEM-utility data exchanges. Full article

Temperature has a significant impact on the operation and performance of electronic systems. Conventional approaches focus on stabilizing electronic systems to maintain functionality under unfavorable thermal conditions, typically at the expense of increased consumption. This paper adopts a multi-objective approach to identify the Pareto-optimal (PO) trade-off across varying temperatures between functionality and consumption of low-power radio transceivers used in the Internet of Things (IoT) and wireless sensor networks. Building upon the established two-segment PO trade-off controlled by supply voltage and output power settings, between engaged and achieved transmission power, parameters directly associated with energy consumption and transmission quality, we analyze the influence of temperature on the Pareto front. We find that decreasing the temperature improves both engaged power and achieved transmission power simultaneously. Therefore, we propose a novel Pareto-optimal temperature-opportunistic wireless communication approach that exploits temperature variability by selecting favorable temperature conditions for transmission. We also identify the spatio-temporal potential of temperature variations across a four-dimensional network deployment space, particularly in temperature-dynamic urban environments of smart city infrastructure supporting massive IoT. Experiments on a modern Texas Instruments CC1200 transceiver confirm that the power savings of approx 30% and nearly 450 times increase in achieved transmission power are attainable for a temperature difference of 60 °C, corresponding to realistic conditions between the ambient air and a black-painted surface. Full article

Energy consumption is a critical concern for Internet of Things (IoT) platforms lacking abundant resources, particularly for swarm robotic systems that rely on numerous devices operating collaboratively over extended periods. This study presents a comprehensive design strategy for improving processing and communication to enhance system efficiency and reduce energy consumption. We incorporate energy harvesting (photovoltaic and RF), dynamic power management, and energy-efficient communication protocols (e.g., duty cycle, power control, data compression) into two complementary platforms built for swarm robotics: MCU-based nodes (TI MSP430 with LoRa transceiver), which serve as the experimental prototype for validating energy-aware communication, compression, and scheduling mechanisms; edge platforms (Jetson Nano and TX2), which are used for high-level power profiling and system-level evaluation, particularly for computation intensive workloads and comparative analysis. Our technique involves analyzing the device’s energy usage and harvesting processes, developing efficient communication protocols, and validating the system through simulations and hardware prototypes. Experimental results under outdoor and indoor conditions show that the device maintains an energy neutrality ratio well above unity, even with limited ambient energy. Key findings include significant reductions in energy per bit transmitted and reliable long-term operation. These insights pave the way for deploying swarms of autonomous IoT-based robots with minimal maintenance and maximal longevity. Full article

Geothermal exploration and monitoring often require dense temperature observations in terrains where wired networks are impractical and battery replacement for in situ sensors is costly. This paper proposes an infrared-assisted, temperature-aware access scheme for a UAV-enabled backscatter IoT network tailored to geothermal hotspot sensing. A rotary-wing UAV equipped with a thermal infrared camera and an RF transceiver first surveys the area to construct a surface temperature map and identify candidate hotspots, and then hovers above a selected hotspot to perform periodic frames consisting of wireless energy transfer followed by backscatter uplink collection. Ground sensors harvest RF energy, measure their local temperature, and autonomously activate only when both the harvested energy exceeds a threshold and the measured temperature falls within a target interval broadcast by the UAV, thereby concentrating channel access on thermally relevant nodes. We develop a system model that couples a geothermal-like thermal field, RF energy harvesting, and framed slotted backscatter access, and introduce hotspot-oriented performance metrics including effective hotspot throughput, task completion time, and energy per hotspot report. The simulation results show that the proposed temperature–energy-gated access significantly increases the fraction of successfully decoded packets originating from hotspot regions and improves the energy efficiency of geothermal monitoring compared with full activation and purely energy-based activation. Full article

The deployment of robust Internet of Things (IoT) networks within smart buildings requires a thorough understanding of radio propagation in complex indoor environments. Long Range (LoRa) technology is a promising solution for such applications due to its long range and low power consumption. However, its performance in multi-floor structures is heavily influenced by site-specific propagation conditions. This paper presents an empirical characterization of LoRa signal propagation at 433 MHz within a four-story university building. Extensive measurements of Received Signal Strength Indicator (RSSI) and Signal-to-Noise Ratio (SNR) were conducted to model both large-scale and small-scale fading effects. A log-distance path loss model with a Floor Attenuation Factor (FAF) was derived, yielding a path loss exponent of $n=2.53$, an FAF of $5.52$ dB per floor, and a log-normal shadowing standard deviation of $\sigma =6.93$ dB. Time-varying small-scale fading was successfully characterized by a Markov-modulated process (Markov Small-Scale Fading). Furthermore, a non-linear relationship between RSSI and SNR was identified and modeled using a four-parameter logistic function, revealing a dynamic range of approximately 30 dB for the transceivers and a minimum measurable RSSI of −125 dBm. The results validate the proposed models and demonstrate that LoRa can provide reliable, building-wide wireless sensor coverage, offering essential guidelines for the planning and deployment of indoor IoT infrastructure in multi-floor environments. Full article

This paper presents an all-digital fractional-N phase-locked loop (ADPLL) operating in the 2.86–3.2 GHz range, optimized for IoT and high-frequency RF transceiver applications demanding stringent phase noise performance, fast settling time, and high integration capability. The key innovation lies in the introduction of a bandpass delta-sigma time-to-digital converter (BPDSTDC) that achieves high-resolution phase detection, an extended detection range of ±2$\pi$, and superior noise-shaping characteristics, completely eliminating the complex calibration procedures typically required in conventional TDC designs. The proposed architecture synergistically combines the BPDSTDC with digital down-conversion blocks to extract phase error at baseband, a divider chain integrated with phase interpolators achieving 1/4 fractional resolution to suppress in-band quantization noise, and a wide-bandwidth digital loop filter (>1 MHz) ensuring fast dynamic response and robust stability. The bandpass delta-sigma modulator is implemented with compact resonator structures and a flash quantizer, achieving an optimal balance among resolution, power consumption, and silicon area. The incorporation of highly linear phase interpolators extends fractional frequency synthesis capability without requiring complex digital-to-time converters (DTCs), significantly reducing design complexity and calibration overhead. Fabricated in a 180-nm CMOS technology, the proposed chip demonstrates robust measured performance. The band-pass delta-sigma TDC achieves a low integrated rms timing noise of 183 fs within a 1-MHz bandwidth. Leveraging this low TDC noise, the complete ADPLL exhibits a measured in-band phase noise of −120 dBc/Hz at a 1-MHz offset for a 3.2-GHz output frequency while operating with a loop bandwidth exceeding 1 MHz. This corresponds to a normalized phase noise of −216 dBc/Hz. The system operates from a 1.8-V supply and consumes 10 mW, achieving competitive performance compared with prior noise-shaping TDC-based all-digital PLLs. Full article

Energy efficiency is a key requirement for Internet of Things (IoT) nodes, particularly in applications powered by energy harvesting that operate without batteries. In this work, we present a parametric power model of a LoRa transceiver (Semtech SX1276) aimed at ultra-low power remote sensing scenarios. The transceiver was characterized in all relevant states (startup, transmission, reception, and sleep), and the results were used to build a state-based model that predicts average power consumption as a function of transmission power, sleep strategy, packetization, and input data rate. Experimental validation confirmed that the cubic fit for transmission peaks achieves a determination coefficient of 0.99, while reception is added as a constant consumption. The model was implemented in a Python simulator that provides mean, best-case, and worst-case estimates of system power consumption, and it was validated in an ASIC-based sensor node demonstration, with predictions within 10% of measured values. The framework highlights the trade-offs between energy efficiency and robustness (e.g., minimal SF and no CRC vs. higher spreading factors and error-control) and supports the design of custom controllers for ultra-low power IoT nodes as well as more energy-permissive applications. Full article

Narrowband Internet of Things (NB-IoT) was designed as a key Low-Power Wide-Area Network technology when 5G networks were established. The ideal quadrature demodulation in NB-IoT relies on the fundamental symmetry between the in-phase (I) and quadrature (Q) branches, characterized by a perfect 90-degree phase shift and matched amplitude. However, practical hardware imperfections in mixers, filters, and ADCs break this symmetry, leading to I/Q imbalances. Moreover, I/Q imbalance is coupled with carrier frequency offset (CFO), which arises from asymmetry in the frequency of the transceiver oscillator. In this paper, we propose a model-embedded lightweight network for joint CFO and I/Q imbalance estimation for NB-IoT systems. An I/Q imbalance compensation model is embedded as a layer to connect two subnetworks, I/Q estimation network (IQENET) and CFO estimation network (CFOENET). By embedding the physical model, the network gains the capability to learn the features of coupling effects during the training process, as the image signals caused by I/Q imbalance are removed before CFO estimation. A phased training strategy is also proposed. In the first phase, the two subnetworks are pre-trained independently. In the second phase, they are fine-tuned jointly to deal with the coupling effects. Simulation results show that the proposed network achieves high estimation accuracy while maintaining low complexity. Full article

This work presents the development and evaluation of a low-cost and low-power IoT system for monitoring slope instabilities, rockfalls, and landslides using LoRa communication. The prototype integrates commercial ESP32-based hardware with an SX1276 transceiver, a triaxial MEMS accelerometer, and a GPS module for real-time tilt and location measurements. A tilt-estimation expression was derived from accelerometer data, enabling adaptation to different terrain inclinations. Laboratory tests were performed to validate the stability and accuracy of the inclination measurement, followed by outdoor LoRa range tests under mixed line-of-sight conditions. A lightweight dashboard was implemented for real-time visualization of GPS position, signal quality, and tilt data. The results show reliable tilt detection, consistent long-range communication, and low power consumption, highlighting the potential of the proposed prototype as a scalable and energy-efficient tool for geotechnical monitoring. Full article

This paper presents a 0.8 V low-power CMOS voltage-controlled oscillator (VCO) with a wide tuning range, fabricated using a TSMC 0.18 μm process. The proposed design incorporates body-biasing techniques and an optimized varactor structure to achieve a tuning range of 1124 MHz (5.829–4.705 GHz) and low phase noise of −117.6 dBc/Hz at a 1 MHz offset. Operating at an ultra-low supply voltage of 0.8 V, the VCO consumes only 3.4 mW, demonstrating excellent power efficiency. A buffer circuit is also employed to enhance output symmetry and suppress flicker noise without introducing additional control complexity. With a figure-of-merit (FOM) of −188.6 dBc/Hz and a wide tuning range of 22.2%, the proposed VCO is well-suited for modern low-power communication systems, including 802.11ac, 5G transceivers, satellite links, and compact IoT devices. Full article

There are over 300 million smart homes worldwide and 60.4 million smart homes in the US, using devices like smart thermostats, smart plugs, smart door locks, etc. Yet in this age of smart and connected devices, we still use paper-based sticky notes on doors to display messages such as “Busy, do not disturb”, “In a Zoom meeting”, etc. In this project, a novel IoT-connected digital sticky note system was developed where the user can wirelessly send messages from a smartphone to a sticky note display. The sticky note displays can be hung on the doors of offices, hotels, homes, etc. The display could be updated with the user’s message sent from anywhere in the world. The key design challenge was to develop the display unit to consume as little power as possible to increase battery life. A prototype of the proposed system was developed comprising ultra-low-power sticky note display units consuming only 404 µA average current and having a battery life of more than six months, with a Wi-Fi-connected hub unit, an MQTT server, and a smartphone app for composing the message. Full article

The development of technologies using the Internet of Things (IoT) concept evolves daily. These numerous technologies, such as LoRa (Long Range) transceivers, find applications in various domains, including monitoring natural disasters and those caused by human error. Security vulnerabilities arise concurrently with the advancement of these new technologies. Cyberattacks seeking to disrupt device availability, such as denial-of-service (DoS) attacks, can effectively exploit vulnerabilities in LoRa devices, hindering disaster monitoring efforts. Therefore, our goal is to assess the network parameters that impact the development of a disaster monitoring environment using LoRaWAN. Specifically, we aim to identify the parameters that could result in network availability issues, whether caused by malicious actors or configuration errors. Our results indicate that certain LoRa network parameters (collision checks, packet size, and the number of nodes) can significantly affect network performance, potentially rendering this technology unsuitable for building robust disaster monitoring systems. Full article

Built indoor IoT-based urban farms successfully combine the cultivation of fresh vegetables with attractive architectural designs. Moreover, implementing IoT-driven urban agriculture requires installing multiple IoT devices containing sensors, controllers, transceivers, and antennas for real-time data transmission. In this context, several factors, including the height of the IoT device above the soil level and the water content in the soil, can affect antenna performance and, consequently, the propagation of radio waves. This paper presents the results from numerical and experimental studies that evaluate the impact of soil on the performance of a monopole antenna for three different antenna positions relative to the soil in a pot and two soil water contents, presented by twelve scenarios. The results show that the antenna has a stable performance in six of the twelve scenarios, with a minimal shift in the resonant frequency of 3% and a narrowing of the frequency bandwidth by 2% compared to the antenna in free space. In the worst-case scenario, the antennas demonstrate a reduction in radiation efficiency of 44%, with the frequency bandwidth narrowing by up to 14% for the antenna fabricated on a PLA substrate and up to 17% for the one built on a foam board substrate. Full article

Energy harvesting technologies are becoming increasingly popular as potential sources of energy for Internet of Things (IoT) devices. Magnetic field energy harvesting (MFEH) from current-carrying components, such as power cables, represents a particularly promising technology for smart grid, infrastructure, and environmental monitoring applications. This paper presents a single-stage AC/DC power converter, a control architecture, and an energy harvester design applicable to MFEH devices. The power converter consists of a MOSFET full bridge that is used to actively rectify the induced voltage at the transceiver while providing a regulated output voltage. The approach is suitable for a broad range of grid power lines, offering a compact power stage that achieves a reduction in component count while active rectification minimizes energy losses, thereby improving thermal management in power electronics compared with the previous research. The experimental results demonstrate that the power converter provides a stable energy source and offers an alternative to self-powering smart grid IoT devices. Full article