Waste facility traffic analytics
Real-time data insights for smarter operations.
Queue spillback onto public roads is a symptom. The cause is a lack of real-time visibility into what is forming at the gate.
Wait times at waste management facilities can range from two minutes to over an hour. Without real-time visibility, staff find out about congestion when vehicles are already stacking onto city streets. SMATS gives operators live queue data as congestion forms and public-facing wait times so residents can decide before leaving home.
Queue visibility is limited until congestion is already on the street
When wait times spike, vehicles stack onto city streets before anyone inside the facility knows. By the time a complaint arrives, the queue is already a safety problem. Real-time queue monitoring gives staff visibility as congestion forms, not after.
Residents driving to the facility without knowing wait times concentrates peak demand
Without live wait time information, residents arrive at peak times regardless, concentrating demand and amplifying spillback. Displaying live wait times on a public-facing dashboard changes behaviour before arrival. Residents self-select to less busy times or alternative sites without any staffing increase.
Leadership and council need documented evidence, not anecdotal reports
Requests for additional staffing or capital funding are stronger when backed by timestamped, independent data rather than estimates and complaint logs. Historical trend data from iNode distinguishes structural capacity problems from temporary spikes and supports before/after comparisons when operational changes are made.
Our solutions
Gate wait times and turn times in real-time
- Install TrafficXHub sensors at site entry and scalehouse to measure how long each vehicle waits to enter the gate and spends on-site, updated every minute
- Use iNode to track real-time, predictive, and historical wait times to spot inefficiencies early and adjust operations proactively
- Build live dashboards to give site operators visibility into queues at any moment
- Leverage historical data to identify peak usage hours, backup points, and turnaround delays to optimize signage and staffing
Turnaround time and full-service tracking
- The same sensor configuration tracks full turnaround time (facility entry to exit) at no additional hardware cost
- Full-service time combines wait time and service time into a complete picture of each vehicle's experience at the facility
- Identifies where time is being lost, whether in the queue before the scalehouse or inside the facility during service
Public-facing wait time display
- Live wait times published via iNode API to your public website via iFrame, always current with no manual updates required
- Green/yellow/red indicators give residents a clear read of site conditions before they leave home
- Residents self-select to less busy times or alternative sites, reducing peak demand without physical changes to the facility
- Reduces inbound complaints by giving the public accurate information before arrival
Real-time congestion alerts
- Automated email or message sign alerts when wait times exceed predefined thresholds
- Operations staff know about queue build-up as it forms, not when the phone starts ringing
- Alert thresholds fully configurable based on site conditions and operational priorities
Seamless system integrations
- Microsoft Power BI dashboards for reporting and leadership visibility
- Variable message signs (VMS) for real-time public communication at or near the facility
Operational value and strategic value from the same data
The same real-time queue and wait time data that helps operations staff manage same-shift decisions also provides leadership with the documented evidence they need for capital planning, budget justification, and public accountability.
Act on data as conditions change, not after complaints arrive
- Real-time queue visibility so staffing adjustments happen same-shift, not next day
- Early warning before queues spill onto public roads
- Fact-based responses to resident complaints backed by timestamped wait time records
- Lane utilisation and throughput data to match staffing to actual demand patterns
Turn operational data into a defensible asset for planning and accountability
- Public-facing wait times reduce peak demand concentration without staffing increases or facility expansion
- Independent timestamped data to respond to council questions and public scrutiny with facts
- Historical trends to support capital funding requests, infrastructure redesign cases, and budget justification
Our approach
Anonymous by design
TrafficXHub sensors passively detect anonymized Bluetooth and Wi-Fi signals. No images, no personal information, no opt-in required. All data is anonymized at point of detection, compliant with GDPR and applicable privacy standards.
Pre-scalehouse queue visibility
Most facility systems capture transaction data at the scalehouse but provide no visibility into the queue forming before it. SMATS adds sensors upstream, giving operators the pre-scalehouse data that existing systems cannot provide.
Load balancing without expanding the site
Live wait times on public-facing dashboards give residents the information to self-select to less busy times or facilities. Demand distributes more evenly across the day without additional staffing or infrastructure changes.
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