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REVIEW 3 major objections 5 minor 107 references

Design of Wireless Sensors for IoT with Energy Storage and Communication Channel Heterogeneity

T0 review · 3 major / 5 minor · reviewed 2026-08-14 · deepseek-v4-flash

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Pith's one-line read A single measured radio burst determines the supercapacitor size for a hybrid IoT sensor supply, reported here as 0.6 µF.

desk verdict The claimed 0.6 µF supercapacitor sizing is off by about two orders of magnitude from the paper's own equations, but the transceiver current data is real and worth preserving. read the letter →

arxiv 1908.09088 v1 pith:K27F25VK submitted 2019-08-24 cs.NI

Paul N. Borza , Mihai Machedon-Pisu , Felix G. Hamza-Lup This is my paper · ORCID
classification cs.NI
keywords wirelesssensornodesautonomoussensorshybridenergystoragesystemsupercapacitorsizingBluetoothLowspectrumcoexistencemanagementinternetofthings
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper tries to establish a holistic design recipe for autonomous IoT wireless sensors in which two transceivers and a hybrid power source (battery plus supercapacitor) work together to improve energy efficiency. The central practical claim is that the supercapacitor can be sized from a single measured current waveform of the transceiver: identify the main active interval, extract its energy $W_{e1}$, and compute the capacitance from a closed-form energy-balance formula. The paper derives $C_{\mathrm{equiv}} = 2.66 W_{e1}/(V_{\max}^2 - V_{\min}^2)$ and reports a value of $0.6\,\mu\mathrm{F}$ for its tested HC-05 transceiver, with the supercapacitor absorbing bursts so the battery sees smoother current and voltage. If this works, designers could choose the storage element from one lab measurement rather than iterative prototyping, and battery life would improve because fast current spikes no longer age the battery.

What carries the argument

The load-bearing identity is Equation (10), $C_{\mathrm{equiv}} = 2.66 W_{e1}/(V_{\max}^2 - V_{\min}^2)$, a closed-form sizing rule derived from the capacitor energy relation $W = \frac{1}{2} C U^2$. The factor $2.66$ comes from writing $W_{e1} \ge 0.75 W_{\mathrm{SC}}$ (so $W_{\mathrm{SC}} = 1.33 W_{e1}$) and then solving $\frac{1}{2} C (V_{\max}^2 - V_{\min}^2) = 1.33 W_{e1}$. The machinery also includes the time-interval decomposition of the current waveform - active maximum, wake/sleep, active minimum - and the constraint that the battery recharges the supercapacitor to $V_{\max}$ in the quiet interval; together these turn one oscilloscope measurement into a component value.

What would settle it

Take the HC-05 current burst the paper measures (roughly 40-65 mA over about 1 ms at 5 V), integrate it to obtain $W_{e1}$, then evaluate Equation (10) with $V_{\max}=3.6$ V and $V_{\min}=1.8$ V; if the result is not near $0.6\,\mu\mathrm{F}$, the reported value is not reproducible from the paper's own data. A bench check would then charge a $0.6\,\mu\mathrm{F}$ capacitor to 3.6 V, connect it to the HC-05 during a burst, and observe whether the voltage stays above 1.8 V; if it collapses, the sizing rule or its assumed energy ratio fails.

Watch

Extended reading notes

Core claim

The authors claim that duplicating both the communication path and the storage path - BLE for short range inside the 2.4 GHz ISM band, nRF24 outside it, and a battery-supercapacitor hybrid supply - yields a measurable gain in energy efficiency. The sizing methodology is the mathematical core: from the time diagram of a Bluetooth transceiver's current draw, four intervals are distinguished, and for the most active interval $T_1$ the energy $W_{e1}$ is assumed to represent at least 75% of the supercapacitor's stored energy. With the voltage window $V_{\max}=3.6$ V to $V_{\min}=1.8$ V (half of $V_{\max}$), the capacitance follows from $W = \frac{1}{2} C U^2$ as $C_{\mathrm{equiv}} = 2.66 W_{e1}/(V_{\max}^2 - V_{\min}^2)$, which the paper evaluates to $0.6\,\mu\mathrm{F}$. The companion operational claim is that the battery must recharge the supercapacitor back to $V_{\max}$ during the low-activity interval, and that this smoothing, together with dual-transceiver communication, avoids accelerated battery aging and supports energy harvesting.

Load-bearing premise

The whole sizing method presumes that the energy used by the transceiver in its main active interval is known and is at least three-quarters of what the supercapacitor stores, and that the capacitor is allowed to swing from 3.6 V down to half that, 1.8 V; if those numbers are not right for a given transceiver, the calculated capacitance changes.

Editorial extensions

If this is right

  • A designer who measures the transceiver's current burst can size the supercapacitor directly from $C_{\mathrm{equiv}} = 2.66 W_{e1}/(V_{\max}^2 - V_{\min}^2)$, skipping iterative simulation.
  • Smoothing the burst with a supercapacitor keeps the battery's delivered current close to constant, which should extend battery cycle life because the method targets rapid current variation as the aging stress.
  • Dual-transceiver operation (BLE in the 2400-2420 MHz sub-band, nRF24 in the 2480-2525 MHz band) offers a coexistence strategy that keeps throughput loss below about 20% in the tested scenarios.
  • Payload and protocol choices matter on the order of 7-30% in energy, so the same hardware can be tuned per application by selecting data payload extremes and transceiver type.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A natural test of the scaling assumption is to apply the same formula to HM-10 (BLE) and JDY-30 (BT) using the paper's own Table 7 energies; the formula predicts different capacitances per transceiver, and a bench test comparing those predictions with measured voltage sag would isolate whether the 75% ratio is the right rule.
  • The 0.6 microfarad result appears difficult to reconcile with the measured 40-65 mA bursts; recomputing from the same data with typical burst durations yields values in the tens of microfarads, which would place the required storage at conventional supercapacitor sizes rather than on-chip graphene capacitors.
  • The same voltage-window reasoning could be turned into a battery-side constraint: the quiet-interval recharge condition gives a lower bound on battery internal resistance, offering a second sizing output for the hybrid supply.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. The paper proposes a design methodology for IoT wireless sensor nodes that combine two transceivers (BT/BLE and RFM) and a hybrid power supply (battery plus supercapacitor). It reports experimental current and energy measurements for HC-05, JDY-30, HM-10, and NRF24L01 transceivers, analyzes band coexistence and 3D emission fields, and derives a sizing formula for the supercapacitor (Eq. (10)). The central quantitative claim is that the calculated equivalent capacitance Cequiv reaches 0.6 µF, and the conclusions state that the developed methodology enables optimal supercapacitor sizing.

Significance. If correct, the methodology would allow a designer to size a hybrid supply from a single measured transceiver current waveform, which is an attractive practical goal. The paper's strengths include a substantial set of empirical transceiver current/energy measurements (Tables 5-8, Figures 9-18), a concrete dual-transceiver testbed, and an explicit energy-balance derivation rather than a purely abstract model. The sizing derivation itself is not circular in the formal sense: Eq. (10) is a direct energy-balance calculation from the measured We1. However, the reported numerical result is internally inconsistent with the paper's own equations and data. The claimed 0.6 µF value is roughly two orders of magnitude below the value obtained by substituting the stated We1 and voltage window into Eq. (10). Because this value is the paper's central quantitative deliverable, the inconsistency is load-bearing and undermines the claim of optimal supercapacitor sizing.

major comments (3)
  1. [Section 7, Eq. (10) and Table 8] The claimed value Cequiv = 0.6 µF does not follow from the paper's own equations. Equation (10) is Cequiv = 2.66·We1/(Vmax²−Vmin²). With the stated Vmax = 3.6 V and Vmin = 1.8 V, the denominator is 9.72 V². For the HC-05 transceiver, Table 8 lists the T1 energy as 204,703 µJ, which in the decimal-comma convention used elsewhere in the paper means 204.703 µJ. Substituting gives Cequiv ≈ 56 µF, not 0.6 µF; for HM-10 (80.501 µJ) the result is ≈ 22 µF. No plausible unit reinterpretation (e.g., treating 204,703 as 204703 µJ, or using Vmin = 0) yields 0.6 µF. This is an internal arithmetic inconsistency in the central result, not a matter of disagreement with external consensus.
  2. [Section 7, assumptions (a) and (c)] The voltage window is chosen without physical justification and directly controls the result. The text first states Vmin = 1.6 V and Vmax = 3.6 V, then replaces Vmin with Vmax/2 = 1.8 V, with no circuit-level reason given. Since Cequiv scales as (Vmax²−Vmin²)⁻¹, this assumption alone changes the capacitance by more than a factor of two relative to the initially stated 1.6 V lower bound. The authors should justify the 50% depth-of-discharge window or provide a sensitivity analysis over the allowable voltage range.
  3. [Section 7, Eq. (6) and validation] The sizing methodology is not experimentally validated. The 75% energy ratio in Eq. (6) is asserted as a design choice, and no measurements of supercapacitor voltage, battery current, or battery stress are reported for a hybrid prototype. The paper's conclusion that hybridization 'generates an improvement in energy efficiency' is therefore not supported by the presented data; at most it is a plausible qualitative expectation. A validation experiment or a clear statement that the hybrid supply was not implemented is needed before the 'optimal sizing' claim can be assessed.
minor comments (5)
  1. [Table 8] The use of a comma as a decimal separator in entries such as '204,703' is inconsistent with the rest of the paper and is a source of ambiguity; use '204.703' (or state the convention explicitly) so that the reader can reproduce Eq. (10).
  2. [Figure 21 and Table 8] The time intervals T1-T4 are defined with t4 = 2400 µs, while the tables refer to a 2500 µs period; the relationship between the measured interval and the total transmission period should be clarified.
  3. [Equations (12)-(15)] Variables such as RESRSC, RIB, and RE are used without definition in the text; define them or label them in Figure 22.
  4. [Abstract and Conclusions] The phrase 'duplicates the transceivers and also the power source' overstates the architectural novelty; a quantitative comparison with prior hybrid energy storage system (HESS) designs would help position the contribution.
  5. [Section 6.2, Tables 5 and 6] The current values use a comma as a decimal separator in some places and a period in others; unify the notation throughout the paper.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the super-capacitor sizing formula is a direct energy-balance calculation from measured transceiver energy; the reported 0.6 µF value is an internal numerical inconsistency, not a circular reduction.

full rationale

The central sizing procedure in Section 7 is not circular in the formal sense. Equation (10), Cequiv = 2.66·We1/(Vmax² − Vmin²), is obtained by combining the explicitly stated hypotheses We1 ≥ 0.75·WeSC (Eq. 6), WeSC,min = 1.33·We1 (Eq. 7), and the stored-energy relation WeSC = ½·C·U² (Eq. 8). This is a transparent energy-balance calculation. The transceiver energy We1 comes from the paper's own measured current waveforms integrated in Section 6.3 (Eqs. 1–4), so the sizing uses measured data as an input rather than redefining a fitted parameter as a prediction. The choices Vmin = Vmax/2 = 1.8 V and the 75% ratio are stated assumptions; conditional assumptions do not make a derivation circular, though they affect validity. The claimed result 'The calculated value for Cequiv reaches 0.6µF' does not follow from Eq. (10) with the numbers in Table 8: for HC-05, T1 ≈ 204.7 µJ, Vmax = 3.6 V and Vmin = 1.8 V give Cequiv ≈ 56 µF, not 0.6 µF. This is a serious internal numerical inconsistency and a correctness/verification problem, but it is not a circularity: the result contradicts the paper's own equation rather than being equivalent to its inputs by construction. The self-citations in the paper ([105]–[107]) support background material and IoT applications, not the load-bearing sizing derivation, so no self-citation chain forces the main result. Under the stated rules, an arithmetic mismatch should be reported as a correctness risk, not as circularity. Consequently, no circular step is identified and the circularity score is 0.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

The central sizing result depends on measured energy inputs and several hand-picked ratios, voltage bounds, and resistance values. No new physical entity is introduced; the contribution is a design calculation.

free parameters (4)
  • We1 energy ratio threshold = 0.75
    Equation (6) sets We1 to at least 75% of the supercapacitor energy to keep the voltage between 100% and 50%; no physical justification is provided.
  • Vmin supply window = 1.8 V
    Hypothesis (a) in Section 7 sets Vmin = Vmax/2 = 1.8 V by hand; changing this bound changes Cequiv.
  • Switch on-resistance RSWON = 0.3 ohm
    Section 7 hypothesis (c) assumes RSWON = 0.3 ohm for the analogue switch.
  • Time interval boundaries t1-t4 = 950, 1150, 1850, 2400 microseconds
    Taken from the measured HC-05 waveform and used to partition the energy consumption; the boundaries are specific to one transceiver and one measurement.
assumptions (6)
  • ad hoc to paper Transceiver operates in the supply interval [Vmin,Vmax] with Vmin = Vmax/2
    Section 7 hypothesis (a); no load requirement or regulator constraint justifies this voltage window.
  • domain assumption Battery behaves as an ideal voltage source with internal resistance; transitory regimes are excluded
    Section 7, paragraph before Figure 22; a standard circuit simplification, but it ignores dynamics that matter for spike smoothing.
  • ad hoc to paper We1 must be at least 75% of the supercapacitor energy
    Equation (6); the ratio is chosen to allow a 100% to 50% voltage swing but no source is cited.
  • domain assumption Li-Ion battery SoC window is [3.6 V, 4.2 V]
    Section 7 hypothesis (b); standard for Li-ion but not general across battery chemistries.
  • domain assumption Data payload extremes 00H and 55H bound the number of voltage transitions
    Section 3; a reasonable approximation for digital payloads but not proven.
  • domain assumption Equivalent transceiver series resistance can be derived from the measured current waveform
    Section 7, Figure 21; the derivation depends on the measurement setup and ignores antenna and electromagnetic effects.

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Cite this review

Pith. "Pith review of Design of Wireless Sensors for IoT with Energy Storage and Communication Channel Heterogeneity." pith.science (2026). https://pith.science/paper/K27F25VK

@misc{pith2026190809088,
  author       = {Pith},
  title        = {Pith review of: Design of Wireless Sensors for IoT with Energy Storage and Communication Channel Heterogeneity},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/K27F25VK}},
  note         = {Machine review of arXiv:1908.09088}
}
read the original abstract

Autonomous Wireless Sensors (AWSs) are at the core of every Wireless Sensor Network (WSN). Current AWS technology allows the development of many IoT-based applications, ranging from military to bioengineering and from industry to education. The energy optimization of AWSs depends mainly on: Structural, functional, and application specifications. The holistic design methodology addresses all the factors mentioned above. In this sense, we propose an original solution based on a novel architecture that duplicates the transceivers and also the power source using a hybrid storage system. By identifying the consumption needs of the transceivers, an appropriate methodology for sizing and controlling the power flow for the power source is proposed. The paper emphasizes the fusion between information, communication, and energy consumption of the AWS in terms of spectrum information through a set of transceiver testing scenarios, identifying the main factors that influence the sensor node design and their inter-dependencies. Optimization of the system considers all these factors obtaining an energy efficient AWS, paving the way towards autonomous sensors by adding an energy harvesting element to them.

Figures

Figures reproduced from arXiv: 1908.09088 by the authors.

Figure 1
Figure 1. Autonomous Wireless Sensors (AWS) design and energy efficiency. The paper commences with a survey identifying the AWS’ main parameters, their ranges, and effects on energy efficiency. In this sense, the following steps are considered: 1. Definition and adoption of an appropriate structure and topologyfor the WSN; 2. Decision on the parameters that must be optimized from the energeticperspective; 3. Development of an… view at source ↗
Figure 2
Figure 2. Setup diagram (low resistance=12.22Ω). 4. AWS Design and Implementation Considering the actual stage of wireless technologies development, as well as the implementations mentioned in Section 2, we implemented an AWS capable of supporting a wide range of transceivers. The custom implementation allows built-in measurements of the power consumption in real-time for the corresponding transceivers. The sampling rate can … view at source ↗
Figure 3
Figure 3. Block diagram of the experimental AWS. The AWSs have an ATMega88 micro-controller with 8 kB flash memory and 1 kB SRAM. The sampling period for temperature and humidity can be adjusted by a corresponding command between 1 ms to more than 60 s. The firmware allows integration into network, reliable transfer of [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figures from the paper (20 more)
Figure 4
Figure 4. Figure 4: AWS: (a) Top layer (CPU-ATMega88; RFM transceiver-NRF24 L01, 2.4 GHz; ADC-MCP3428; Temperature Sensor-HTU21D); (b) bottom layer: BLE transceiver—HM10BLE; CS1/CS2-current sensors (ACS 712-05) based on the Hall Effect. 4.2.Software Components The firmware is conceived as…
Figure 5
Figure 5. Figure 5: Test scenarios: (a) Troita Junilor park (Brasov periphery); (b) NII2 building (Brasov center). (a) NII2: 2400–2420 MHz (b) NII2: 2430–2450 MHz (c) HC-05 in (a) (d) NRF24L01 [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]
Figure 6
Figure 6. Figure 6: A room inside the NII2 building. Spectrum bands: (a) Semi-occupied spectrum; (b)occupied spectrum; (c) HC-05 in 2400–2420 MHz band; (d) ISM outer band (unoccupied spectrum), for NRF24L01. In scenarios similar to Figure 6c, we performed spectral analysis for BT/BLE tran…
Figure 7
Figure 7. Figure 7: Measured: (a) MicaZ antenna emission field (dB); (b) HC-05 antenna emission field. The practical measurements confirm the proximity to the theoretical model, however the small differences between the measured and the theoretical model can only be measured visually, by …
Figure 8
Figure 8. Figure 8: Theoretical: (a) MicaZ antenna emission field (dB); (b) HC-05 antenna emission field. The power consumption analysis of the sensors improves the AWS placement such that the sensor autonomy is improved. In this case, we expect sensors to provide data without interruptio…
Figure 10
Figure 10. Figure 10: JDY-30 Current over 10ms for a 12.2Ω resistor (no echo mode) : (a) a command of 100 U (55H) characters sent in burst; (b) a command of 300 U (55H) characters sent in burst; (c) no command was sent; (d) in disconnected state [PITH_FULL_IMAGE:figures/full_fig_p014_10.png]
Figure 11
Figure 11. Figure 11: HM-10 Current over 10 ms for a 12.2Ω resistor (no echo mode) : (a) a command of 50 U (55H) characters sent in burst; (b) a command of 200 U (55H) characters sent in burst; (c) no command was sent; (d) in disconnected state. Considering the form revealed inReference [1…
Figure 13
Figure 13. Figure 13: HC-05 current consumption [A] waveform when “U” characters were transmitted (50 vs. 100) for 1.25 ms. (The spikes were cleaned) (no echo mode) [PITH_FULL_IMAGE:figures/full_fig_p016_13.png]
Figure 14
Figure 14. Figure 14: HC-05 current consumption [A] waveform when null characters were transmitted (50 vs. 100) for 1.25 ms. (The spikes were cleaned) (no echo mode) [PITH_FULL_IMAGE:figures/full_fig_p016_14.png]
Figure 15
Figure 15. Figure 15: JDY-30 current consumption [A] waveform when null characters were transmitted (50 vs. 100) for 2.5 ms. (The spikes were cleaned) (echo mode) [PITH_FULL_IMAGE:figures/full_fig_p016_15.png]
Figure 16
Figure 16. Figure 16: JDY-30 current consumption [A] waveform when “U” characters were transmitted (50 vs. 100) for 2.5 ms. (The spikes were cleaned) (echo mode). The spikes observed for these transceivers are relevant for the total consumption measured in our experimental settlements. The…
Figure 17
Figure 17. Figure 17: JDY-30 current consumption with the inherent spike (50 vs. 100 U transmitted characters) (echo mode) [PITH_FULL_IMAGE:figures/full_fig_p017_17.png]
Figure 18
Figure 18. Figure 18: JDY-30 current consumption without the spike (50 vs. 100 U transmitted characters) (echo mode) [PITH_FULL_IMAGE:figures/full_fig_p017_18.png]
Figure 19
Figure 19. Figure 19: Power drawn by the HM-10, JDY-30, and HC-05 transceivers depending on distance. We observe and prove that there is a dependency between the distance, the data pattern and the power consumption, that is essential for an optimal adaptation to the application or process …
Figure 20
Figure 20. Figure 20: The design commences with the precise identification of the t [PITH_FULL_IMAGE:figures/full_fig_p019_20.png]
Figure 20
Figure 20. Figure 20: storage system circuit. Starting from the time diagram in [PITH_FULL_IMAGE:figures/full_fig_p020_20.png]
Figure 21
Figure 21. Figure 21: Time Diagrams for HC-05: for four successive time intervals [PITH_FULL_IMAGE:figures/full_fig_p020_21.png]
Figure 22
Figure 22. Figure 22: Electric circuits. In all the models, we have considered the battery as an ideal voltage source in the series with the internal resistance. Additionally, we have excluded the transitory regimes from the electrical analysis. For the sizing process, we consider the ener…
Figure 23
Figure 23. Figure 23: Volumetric representations: (a) IoT-based, via 12 or 20 sensors connected to HC-05 transceivers, (b) based on Fluke IR thermal imaging. Additionally, lower cost sensors such as TMP-36z (less than 1 euro) and H5U21D (3 euro) can be used and provide the same accuracy: 2…
Figure 25
Figure 25. Figure 25: Data flows in the system. This structure allows the implementation of local control functions, it is also able to redirect or simply transmit data collected to the supervisor. 9. Conclusions and Future Work This research enables a better understanding of the AWS novel…

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Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.