Aug 2026· Computer Networks and Communications· pp. 245-269· 0 citations
TL;DR
This paper derives the energy model for single-node communication and extends it to multiple-sensor-node communication where several sensors concurrently transmit their information and derives an energy model for a battery-free sensor node that relies on the energy harvested from ambient sources to drive its operation.
Abstract
The integration of Wireless Sensor Networks (WSNs) into Internet of Things (IoT) brings new challenges in terms of range and energy consumption. Specifically, energy consumption is of great importance for future IoT sensors. Therefore, a thorough study must be performed to understand and evaluate the impact of different parameters that affect sensor node energy consumption. However, LoRa backscatter has been seen as a promising technology for long-range low-power IoT applications. Hence, this paper addresses the modeling of the energy consumption of a LoRa backscatter-based sensor node. We first derive the energy model for single-node communication and extend it to multiple-sensor-node communication where several sensors concurrently transmit their information. Furthermore, we derive an energy model for a battery-free sensor node that relies on the energy harvested from ambient sources to drive its operation. The simulation results show that both the LoRa parameters (such as payload size), the number of nodes in the network, and the number of retransmissions can impact the total energy consumption of the sensor node. Additionally, a single node powered by a battery with a capacity of 225 mAh and a transmission of 20 bytes every 5 minutes has a lifetime of about 14 years.
Long Range (LoRa) sensors are widely adopted in Internet of Things (IoT) applications due to their combination of long‐range communication and low energy consumption. However, the continuous, large‐scale operation of these devices raises concerns about cumulative energy consumption and environmental impacts over time. Evaluations based solely on prototypes and field tests tend to be costly, time‐consuming, and poorly reproducible, hindering the systematic comparison of multiple operational scenarios. To address these challenges, this work proposes a mechanism for analyzing the energy consumption and environmental impact of LoRa sensors over time, focusing exclusively on the sensor node. The goal is to support sustainable planning of large‐scale LoRa deployments by enabling the temporal evaluation of battery discharge, transmitted packets, and CO emissions under different message generation rates and physical transmission parameters. The mechanism is developed using Stochastic Petri Nets (SPN), which model the alternation between the operating states of a LoRa sensor. Environmental impact is quantified by converting accumulated energy consumption into CO emissions using a global average carbon emission factor. The SPN model is cross‐validated against a discrete‐event simulation implemented in NS‐3. The cross‐validation indicated close agreement between the SPN model and NS‐3, with mean absolute percentage errors below 0.3% across all evaluated metrics. The packet generation rate is shown to govern both sensor lifetime and the temporal distribution of CO emissions, with the per‐packet carbon footprint increasing under low‐traffic scenarios due to the higher share of idle consumption. The Spreading Factor (SF) exhibits a monotonic effect on energy consumption, per‐packet CO, and battery drain, with SF12 emitting approximately 8.55 times more CO per packet than SF7. When projected to networks of thousands of devices, this behavior produces a multiplicative effect on the collective carbon footprint. Ultimately, a multidimensional analysis via a radar chart illustrates the trade‐offs among lifetime, energy efficiency, data throughput, and carbon footprint across the evaluated scenarios. The proposed SPN‐based model effectively characterizes the temporal evolution of energy consumption and environmental impact of LoRa sensors, revealing cumulative dynamics that average metrics or isolated final values would not capture. This transient analysis demonstrates that sustainability assessment in LoRa networks must consider the interactions among active consumption, reception overhead, residual idle drain, and information density throughout the device's operational cycle, providing a reliable basis for early scenario evaluation and energy‐aware planning for large‐scale IoT deployments.
Vandirleya Barbosa, Melissa Alves, I. Almeida et al.· International Journal of Com...· 0 citations
Recent demand for Internet of things (IoT) based sensing devices has increased in many significant areas, such as greenhouse monitoring, remote patient monitoring, military applications, wild-life tracking and habitat monitoring, precision agriculture, etc. Moreover, some critical issues are present in the perpetual sensor network like node energy consumption rate, coverage/connectivity, quality of service, network throughput and charging cycle capacity of sensor node batteries. Thereby, various network issues can arise, especially regarding coverage holes, proper connectivity, and network life-time. In this paper, we have studied these problems well and have shown the necessary constraints for the connectivity of the IoT sensor network. Moreover, we have also presented various helpful IoT applications and energy harvested IoT sensor networks. Any network can perform well for a long time because of energy management which is very crucial. This paper presents various feature scopes used in wireless sensor networks (WSNs). It also illustrates distinct approaches like relay node placement, efficient communication, machine-learning systems i.e. reinforcement learning, and heuristic techniques. It also discusses real-world deployments to highlight practical connectivity challenges and failures.
Ramesh Kumar, D. Sah, R. Bhan· Peer-to-Peer Networking and...· 0 citations
An analytical framework for evaluating the outage probability of ambient Internet of Things device classes communicating directly with a base station is presented and it is highlighted that the optimal device choice depends critically on the operating regime and application demands.
Azzam Al-nahari, R. Jäntti, Yi Zhou et al.· 0 citations
With the rapid proliferation of Internet of Things (IoT) devices and advancements in low‐power technologies, radio frequency (RF) energy harvesters present an economical and convenient power solution for low‐power wireless sensor nodes (WSNs). The limited utilization of ambient energy in current RF self‐powered WSNs is primarily due to inadequate spectrum coverage. This research proposes an ambient RF energy powered WSN to monitor environmental temperature, humidity, and atmospheric pressure. An integrated broadband Vivaldi rectenna has been developed to harvest RF energy across the 1.8 to 2.45 GHz range, utilizing an impedance matching network (IMN) based on conjugate‐complex techniques alongside a tuning network that collaboratively enhances broadband rectification. The maximum power conversion efficiency (PCE) of the rectifier reaches 61% at an input level of 0 dBm. The system demonstrates sustainable operation at a distance of 16.15 m from a directional RF source. These remarkable results underscore the promising potential of the proposed system as a self‐sustainable and cost‐effective solution for IoT applications with low power requirements.
Tiancong Wang, Yu Cao, Xiaoqiang Liu et al.· Microwave and optical techno...· 0 citations
IoT applications have revolutionized internet utilization to facilitate several aspects of human life. However, it requires high energy efficiency from the sensor nodes, capable of providing corresponding signals over long distances. This motivates the development of LoRa technology aimed at these requirements. The current limitations of LoRa's location and environment should also be considered. Therefore, this paper seeks to analyze the performance of received signal strength and signal quality in both outdoor and indoor environments. LoRa signal measurements are performed by placing the TTGO‐ESP32‐LoRa OLED at various heights and testing with various antennas at the receiver in an outdoor environment. The signal measurement is conducted in the level 3 hostel building at UniKL BMI, Selangor, Malaysia, for indoor environments. The measured data highlighted that the quality of a LoRa network depends on the distance and height at which the signal is transmitted, the antenna selection, and the path loss caused by structural elements. Better outdoor coverage can be improved by increasing the height of the transmitter for both outdoor and indoor environments. This paper highlights that a 5 dBi antenna has enhanced the signal strength up to −85.9 dBm in outdoor environments and −94.61 dBm in indoor environments. These findings underscore the significance of quantified antenna‐related information in design guidelines for optimizing LoRa network deployments in densely populated IoT environments.
Noor Hidayah Mohd Yunus, Syaza Syahirah Ismail, H. Basarudin et al.· Applied Research· 0 citations
This work presents a multi-mode energy harvesting-assisted edge computing architecture, integrated with a joint optimization of energy consumption and communication behaviour, aimed at enhancing the sustainability, reliability and autonomy of operation in an industrial IoT context.
Dr. Deepa, M. Mehfooza, Padmavathy Thiruppathi Raj· Microsystem Technologies· 0 citations
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