Central sterile supply departments (CSSDs) rely on liquid disinfectants for cleaning and pre-sterilization of reusable medical devices. One commonly used disinfectant is acidic electrolyzed oxidizing water (AEOW). Because AEOW, tap water, and purified water are colorless and visually indistinguishable, and AEOW has only a faint chlorine odor often masked by masks, inadvertent use of tap or purified water in place of AEOW can produce ineffective disinfection. Such errors can persist for hours because AEOW solutions in CSSD tanks are reused continuously, amplifying the risk of device contamination.
Standard operating procedures mandate testing pH and available chlorine content (ACC) at AEOW taps prior to use. However, chemical pH/ACC test strips are subjective, cumbersome, and produce medical waste; electronic instruments improve accuracy but increase purchase and calibration burdens. The need exists for an inexpensive, rapid, objective verification tool that fits routine CSSD workflows.
AEOW is produced by electrolysis of sodium chloride or hydrochloric acid solutions and contains abundant ions (Na+, Cl-, H+, ClO-). These ions yield substantially higher electrical conductivity (EC) than purified water (≤15 μS/cm) and typical municipal tap water (~200–400 μS/cm). Literature and field measures indicate AEOW EC commonly exceeds 1000 μS/cm, providing a physical property that can distinguish AEOW from other clear liquids without chemical reagents.
The lighthouse-shaped rapid identification device (LRID) was developed using Arduino technology. Its hardware integrates:
Electronic components and PCBs were wrapped and potted for protection; the EC probe is mounted approximately 2 cm above the device bottom so it remains submerged when AEOW liquid level is ≥5 cm, the typical immersion height for stainless-steel baskets used in CSSDs.
When the LRID is placed into a test solution, liquid enters the device and submerges the EC probe. The adapter board converts probe signals to an analog voltage, which the microcontroller reads via its analog-digital converter (ADC). The embedded program compares the ADC value to a configured threshold and lights LEDs accordingly: continuous green for AEOW (ADC above threshold) and continuous red for non-AEOW (tap or purified water) solutions. The blue LED indicates charging.
This study set the ADC discrimination threshold to 150 after empirical testing and trade-offs. AEOW samples diluted to an EC of 1000 μS/cm produced ADC readings of 207–212 across three LRID prototypes. Tap-water samples with EC values of 278 and 288 μS/cm produced ADC readings of 55–59. Purified water, with EC ≤15 μS/cm, generated much lower ADC values. Theoretical feasible threshold ranges for this configuration are approximately 70–200; a higher threshold (150) was chosen to reduce false-positive classification from high-conductivity cleaning agents while preserving a safety margin.
Three LRID prototypes were fabricated. The integrated PCB (42 × 33 mm) accommodates the microcontroller, a boost converter, LED driving circuitry, and battery charge/discharge management. The EC signal adapter board measures 42 × 32 mm. To improve durability, the PCB and wireless charging module are wrapped with nylon-based tape and all electrical components encapsulated with potting compound. The device’s pushbutton and LED arrangement convey battery status at power-on (red LED plus flashing pattern for remaining battery levels) and operational results when immersed.
In field tests using AEOW, tap water, and purified water samples collected from CSSDs in 10 hospitals, the LRID achieved 100% identification accuracy (90 of 90 samples correctly classified). Measured average battery life was 83.75 ± 1.27 hours, supporting a weekly charging routine. Waterproof performance was validated by continuous immersion in AEOW for 30 days, after which all devices functioned normally.
The LRID’s classification logic worked within observed EC ranges: AEOW EC >1000 μS/cm, tap water typically ~200–400 μS/cm, and purified water ≤15 μS/cm. ADC measurements in prototypes reflected these EC differences (AEOW ADC ~207–212; tap water ADC ~55–59).
Twenty-eight CSSD technicians compared the LRID with the conventional chemical pH test strip method. Across the domains of identification accuracy, ease of operation, and promotability, LRID scored significantly higher than pH strips (P < 0.001). The LRID removes subjective interpretation, reduces consumable waste, and provides immediate visual feedback.
The LRID reported here lacks temperature-compensation in its EC-monitoring module; EC decreases roughly 2% per 1 °C temperature drop. However, CSSD indoor temperatures typically range from 16 °C to 24 °C, and the chosen threshold of 150 maintains a safety margin even with modest temperature variation; for example, an AEOW baseline ADC of 207 would remain above 160 after a 10 °C temperature drop. The authors note that tap-water EC and AEOW EC vary by location and generator model, and ADC spans can differ among EC modules. Therefore, individual CSSDs are advised to calibrate the threshold on-site by modifying a single software parameter in the device code.
Cost is an important practical consideration: the LRID unit can be produced for approximately 20 USD, offering a low-cost alternative to electronic conductivity meters or reliance on subjective test strips.
Limitations explicitly reported in the source include the absence of a temperature-compensation function in the prototype and variability of EC across sites; no long-term multicenter deployment data beyond the described field tests were provided.
The study developed and validated a compact, low-cost lighthouse-shaped rapid identification device (LRID) that discriminates AEOW from tap water and purified water using electrical conductivity. In the tests reported, LRID achieved perfect classification across 90 samples, long battery life compatible with weekly charging, and durable waterproof performance after 30 days’ immersion. The device improved technician-rated accuracy and ease-of-use compared with pH test strips and offers a customizable threshold to match local water and generator conditions. The LRID may reduce disinfection failures caused by liquid misuse in CSSDs while minimizing cost and operational complexity.