Energy Consumption Analysis of LPWAN Technologies and Lifetime Estimation for IoT Application

Singh, R. A.; Puluckul, Priyesh Pappinisseri; Berkvens, Rafael; Weyn, Maarten

doi:10.3390/s20174794

Cited by 92 publications

(68 citation statements)

References 29 publications

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“…In these cases, sensors with minimal power consumption have to be paired with energy-efficient communication technologies to allow maintenance-free operation without an external power source for multiple years. While most customer smart metering applications rely on highly energy-efficient radio technologies (e.g., versions of wireless M-Bus [ 13 ]) in combination with fixed network solutions [ 3 ], increasing coverage of LPWAN technologies [ 4 , 6 , 22 ] offers water utilities new possibilities to operate larger numbers of pressure-monitoring devices for fast leak detection.…”

Section: Methodsmentioning

confidence: 99%

“…To assess energy consumption of the EPMD, a simplified energy consumption model is employed, which was derived from multiple sources on the calculation of GPRS [ 73 ], NB-IoT [ 22 , 74 , 75 ], LoRaWAN [ 22 , 76 , 77 , 78 ] and Sigfox [ 22 , 79 ] energy consumption. Simplifications are based on operational experience with the EPMD and recent publications including analysis and field testing of LPWAN sensors and monitoring devices [ 13 , 27 ].…”

Section: Methodsmentioning

confidence: 99%

“…Measured energy consumptions for the rapidM2M M3 MCU are simplified to mean consumptions for all operating states, as well as mean durations for the operating states monitoring/logging and data transmission ( Figure 3 a). In a similar manner, power consumption and transmission specifications for the three LPWAN technologies, where no measured data was available, were derived from the MCU datasheet [ 71 ] and findings of similar studies [ 22 , 79 ]. By employing this approach, it was possible to include the specifications for all four communication technologies.…”

Section: Methodsmentioning

confidence: 99%

“…For the EPMD configurations in Figure 4 a, the feasibility was assessed individually for each communication technology, based on constraints of the energy consumption model, the encoding of the payload and transmission performance of the communication modules on the MCUs. Further, constraints and technology-specific limitations on payload or package size [ 22 ], as well as hourly device airtime limits or the maximum number of daily transmissions were considered. Since actual transmission rates may vary based on the conditions encountered at the installation site (e.g., inadequate network coverage), data transmission rates based on the values offered in the MCUs data sheets ( Table 3 ) were assumed.…”

Section: Methodsmentioning

confidence: 99%

“…Limitations on data transmission for NB-IoT at a frequency of 200 kHz can be contractual and specific to cellular network carriers. Nonetheless, the maximum payload size for a single NB-IoT transmission is limited to 1600 bytes [ 22 ], a constraint, which was considered by splitting respective transmissions into multiple subsequent bursts, similar to the approach for LoRaWAN.…”

Section: Methodsmentioning

confidence: 99%

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Assessing the Potential of LPWAN Communication Technologies for Near Real-Time Leak Detection in Water Distribution Systems

Pointl

Fuchs-Hanusch

2021

Sensors

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While low-power wide-area network (LPWAN) technologies have been studied extensively for a broad spectrum of smart city applications, their potential for water distribution system monitoring in high temporal resolution has not been studied in detail. However, due to their low power demand, these technologies offer new possibilities for operating pressure-monitoring devices for near real-time leak detection in water distribution systems (WDS). By combining long-distance wireless communication with low power consumption, LPWAN technologies promise long periods of maintenance-free device operation without having to rely on an external power source. This is of particular importance for pressure-based leak detection where optimal sensor positions are often located in the periphery of WDS without a suitable power source. To assess the potential of these technologies for replacing widely-used wireless communication technologies for leak detection, GPRS is compared with the LPWAN standards Narrowband IoT, long-range wide area network (LoRaWAN) and Sigfox. Based on sampling and transmission rates commonly applied in leak detection, the ability of these three technologies to replace GPRS is analyzed based on a self-developed low-power pressure-monitoring device and a simplified, linear energy-consumption model. The results indicate that even though some of the analyzed LPWAN technologies may suffer from contractual and technical limitations, all of them offer viable alternatives, meeting the requirements of leak detection in WDS. In accordance with existing research on data transmission with these technologies, the findings of this work show that even while retaining a compact design, which entails a limited battery capacity, pressure-monitoring devices can exceed runtimes of 5 years, as required for installation at water meters in Austria. Thus, LPWAN technologies have the potential to advance the wide application of near real-time, pressure-based leak detection in WDS, while simultaneously reducing the cost of device operation significantly.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Assessing the Potential of LPWAN Communication Technologies for Near Real-Time Leak Detection in Water Distribution Systems

Pointl

Fuchs-Hanusch

2021

Sensors

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Closed‐form expression of long‐range modulated massive multiple‐input multiple‐output fractional Fourier transform‐orthogonal frequency division multiplexing system under two‐wave with diffuse power fading channel

Chawla,

Kansal

2023

Int J Communication

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SummaryIn this paper, the massive multiple‐input multiple‐output fractional Fourier transform‐based orthogonal frequency division multiplexing (MIMO FrFT‐OFDM) system is investigated using the Long Range (LoRa) modulation technique. The conventional system relies on quadrature amplitude modulated (QAM) modulation technology; high‐power amplifiers are needed to transmit the QAM signal. The LoRa modulation technique produces long‐range and low power signals. The two‐wave with diffused power (TWDP) fading channel is used to examine the system's performance. The expression of the bit‐error rate (BER) of the proposed system is also represented in a unique closed form. The proposed system is applied to a state‐of‐the art hospital, one of the Internet of Things (IoT) applications. As the problem of heart stroke is common, it needs to be monitored every second. The electrocardiogram (ECG) data are used to evaluate how well the proposed system is working. Using the proposed model, the physicians get the patient's ECG data while moving in the hospital, getting it at a high data rate, at a low cost because of the extended battery life, a long range, and a low BER. The data considered are from the MIT‐BIH Arrhythmia Database. The result displays that the proposed model achieves a BER of at 10 dB of signal‐to‐noise ratio (SNR), and the conventional model achieves the same BER at 15 dB of SNR. The BER performance of the proposed system is improved by nearly 5 dB.

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An efficient resource scheduling mechanism in LoRaWAN environment using coati optimal Q‐reinforcement learning

Mahesh,

Mahapatro

2024

Int J Communication

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SummaryIt is estimated that there will be over two dozen billion Internet of Things (IoT) connections in the future as the number of connected IoT devices grows rapidly. Due to characteristics like low power consumption and extensive coverage, low‐power wide area networks (LPWANs) have become particularly relevant for the new paradigm. Long range wide area network (LoRaWAN) is one of the most alluring technological advances in these networks. Although it is one of the most developed LPWAN platforms, there are still unresolved issues, such as capacity limitations. Hence, this research introduces a novel resource scheduling technique for the LoRAWAN network using deep reinforcement learning. Here, the information on the LoRaWAN nodes is learned by the reinforcement technique, and the knowledge is utilized to allocate resources to improve the packet delivery ratio (PDR) performance through a proposed coati optimal Q‐reinforcement learning (CO_QRL) model. Here, Q‐reinforcement learning is utilized to learn the information about nodes, and the coati optimization algorithm (COA) helps to choose the optimal action for enhancing the reward. In the proposed scheduling algorithm, the weighted sum of successfully received packets is treated as a reward, and the server allocates resources to maximize this Q‐reward. The evaluation of the proposed method based on PDR, packet success ratio (PSR), packet collision rate (PCR), time, delay, and energy accomplished the values of 0.917, 0.759, 0.253, 85, 0.029, 7.89, and 10.08, respectively.

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Energy Consumption Analysis of LPWAN Technologies and Lifetime Estimation for IoT Application

Cited by 92 publications

References 29 publications

Assessing the Potential of LPWAN Communication Technologies for Near Real-Time Leak Detection in Water Distribution Systems

Assessing the Potential of LPWAN Communication Technologies for Near Real-Time Leak Detection in Water Distribution Systems

Closed‐form expression of long‐range modulated massive multiple‐input multiple‐output fractional Fourier transform‐orthogonal frequency division multiplexing system under two‐wave with diffuse power fading channel

An efficient resource scheduling mechanism in LoRaWAN environment using coati optimal Q‐reinforcement learning

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