Advancer Smart Technology
Conventional NH3 detectors measure within a range of 1-100 ppm. AST has enhanced this capability to 0.1-100 ppm, allowing it to detect odours that closely represent irritation levels perceived by the human nose. The sensor continuously monitors air quality and sends threshold warnings via the AST notification system. All data is consolidated and processed by the AST AI algorithm for analysis and can be viewed on the AST proprietary dashboard platform. The smart IoT sensor also detects environmental conditions such as humidity, which are continuously monitored.
The human traffic count system forms the pivot solution in a toilet management system, being the first sensor to track users entering the toilet. It correlates with other sensor utilization/tracking rates in the toilet, providing appropriate responses and follow-ups to the service provider. AST adopts various technologies such as body imaging metrology with edge computing technology, Time of Flight (TOF), and Passive InfraRed (PIR) sensors to achieve various levels of human count accuracy (75-99.5%) as required by the customer.
Leveraging its extensive domain knowledge, AST has developed a sensor that detects the status of individual toilet cubicles and provides real-time updates to a feedback panel outside the toilet. This state-of-the-art IoT sensory system achieves over 95% accuracy in detecting cubicle occupancy.
The current practice of changing toilet paper in the cleaning industry leads to high wastage, as cleaners cannot accurately predict when toilet paper will run out. To address this: AST designed a self-feedback toilet paper dispenser that provides real-time notifications to cleaners when replacement is needed. This method has proven to be more efficient. The dispenser is compatible with any size of toilet roll, regardless of brand or model, helping stakeholders save costs and promote sustainability.
Magnetic contact door IoT sensors work using two main parts: a magnet and a switch. One part is attached to the door frame, and the other to the door. When the door closes, the magnet keeps the switch in position. When the door opens, the magnet moves away, and the switch changes position. This change is detected and sent over the IoT network, providing real-time toilet cubicle usage status (occupied/non-occupied).
Conventional user feedback panels allow users to rate their satisfaction with toilet cleanliness. AST has customized panel layouts for stakeholders, enabling real-time display and user feedback. These panels can display videos or newsletters to educate users on maintaining a clean restroom or share news updates. AST integrates the entire toilet sensory network into these panels, giving cleaners easy reference and task tracking.
An occupancy display panel shows the "live" status of toilet cubicles using IoT sensors. Additional IoT sensors monitor various restroom aspects such as soap levels, paper towels, and waste bin levels. These sensors send real-time data to the display panel, ensuring that users and maintenance staff are informed of the current restroom status. This integrated system improves efficiency, cleanliness, and user satisfaction.
The digital toilet gender signage is wirelessly connected to the feedback panel, allowing cleaners to control it during cleaning sessions. When a cleaner starts cleaning, they update their status on the feedback panel, changing the signage background to red (indicating the toilet is temporarily unavailable). Once cleaning is complete, the cleaner updates the panel again, switching the signage back to white (signaling the toilet is available). This system ensures clear communication and enhances user experience with real-time status updates.
The soap dispenser sensor is a non-contact liquid level sensor based on LoRaWAN® technology. It monitors soap levels in restrooms and sends out alarms when the soap level reaches a preset low level. The sensor triggers an alert when the hand wash level reaches the electrode detection strip, indicating low soap levels.
The Bluetooth attendance-taking sensor accurately tracks the cleaner’s schedule as they begin and complete their cleaning tasks. The sensor logs start and end times, transmitting data via LoRa network/4G. A WhatsApp notification is sent to the cleaning supervisor, providing real-time updates on the cleaner's schedule. This ensures efficient management and oversight of cleaning activities.
Cleaners typically empty bins regardless of the fill level to prevent overflow. With the AST SMART algorithm, cleaners are notified to empty bins only when necessary. The system monitors different waste levels and sends a work order notification when the bin is full, optimizing cleaner efficiency. The sensor is IP67-rated, ensuring durability and water resistance.
AST provides a proprietary neural network system and deep learning architecture to ensure that deployed sensors detect clean and accurate data for optimal dynamic cleaning activities. The AI can identify process repetitions and anomalies, delivering results comparable to, or superior to, human supervisors. After 6-12 months of deep learning, the AI progressively assumes responsibility for cleaning assignment and deployment. This moves away from scheduled approaches, improving efficiency and resource allocation.
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