Indoor Positioning Analytics for Smart Warehousing & Yards

How Choosing Indoor Positioning Analytics Transforms Operations

Indoor positioning analytics applying a versatile indoor location analytics and indoor positioning software

Visualising Indoor Positioning Data for Better Decision-Making

• Virtual demarcation of a production shop floor into multiple zones
• Locating lone workers within respective zones created at the construction site
• Visualise the indoor location of these workers on a 2D map using indoor positioning data
• Mapping movement matrices of the workers to improve worker productivity and safety
• Features to analyse the efficacy of the connected workforce concept
• Create go-no-go zones to restrict worker access to hazardous zones
• Initiate alarms to concerned personnel if workers move into restricted areas
• Generate a time-spent report for each worker in different zones
• Reports showing the number of intrusions to restricted areas, along with entry/exit

A. Yard Management: Carrier Turnaround Time (TAT)

• The Pivot Goal: Identify which logistics providers are causing yard congestion.

• Pivot Configuration: * Rows: Asset ID (Filtered for Trailers)

  • Values: Sum of Duration (Converted to Hours)

• Outcome: You can instantly see which trailers have been in the yard for >48 hours, triggering automated alerts to the carrier to avoid demurrage.

B. Warehouse: MHE (Material Handling Equipment) Utilisation

• The Pivot Goal: Optimise the size of your forklift fleet.

• Pivot Configuration: * Rows: Asset Type (Forklift)

  • Columns: Functional Zone

  • Values: Average Duration

• Outcome: If Forklifts are spending 80% of their time in “Aisle 7” but only 5% in the “Cross-docking” area, you can rebalance your fleet to match actual workflow density.

Indoor positioning analytics & indoor location analytics

You can find the above requirements on the RTLS Platform as user-friendly features. The research students tested these features at test facilities simulated within NUS (Singapore), which helped them gather various insights about yard management.

This mainly involved capturing workers’ movement matrices, issuing alerts when workers entered restricted areas, and providing time-spent reports for workers across various zones of the simulated construction site. The insights gathered will be further used in real-world construction sites to ensure improved safety alerts for the workers. The same will also be used to educate concerned construction personnel on techniques to improve site efficiency and productivity.

Using Indoor Location Analytics & Tracking to Optimise Workflow Monitoring

The pivot table consists of fixed variables like date, zone, floor, object name, category, and staff details in its rows, and changeable variables like names of the zones (shop floor, reception, exit way, etc), floors, and cluster names in its columns. The pivot table also provides an environment monitoring option to keep the room’s humidity, temperature, and airflow at optimum levels.

The ultimate feature offered by the indoor positioning data analytics solution is its unique customisation for representing the collected data. The data can be represented either together or in the following ways,

• Visual representation
• Quantitative representation
• Parameter to be represented
• Custom sorting based on zones, login, and logout times
• Shop floor elements drag and drop
• Bluetooth indoor positioning system integrated with Ripples CMMS facilities management software

Visual Representation of Shopfloor Data – The data received from the Bluetooth devices is projected onto the pivot table using visual representation tools. It will be represented in various illustrations (not limited to) such as histogram, box plot, heat map, bar graph, line graph, and frequency table using the best indoor positioning system.

Parameter to be represented – The quantitative data obtained from the sensors is displayed on the pivot table as numerical entries based on various parameters. These parameters can be selected based on needs. The parameters include the time spent in a room, the room’s temperature, the number of persons in a zone, the number of visits made to a zone, etc. If one wants to know the number of visits made by a worker to a particular zone, the parameter to be selected will be visit count, which is customizable.

Quantitative Representation – Once the parameter is decided, the numerical entries can be represented by an array of quantitative parameters. These quantitative arrays include the sum, average, range, median, mode, standard deviation, etc. For example, if the parameter selected is visit count, then the data can be viewed as the sum of the visit counts by a physician, the average of the visit counts, and so on.

Custom Sorting – This is a basic feature tool available in the customisable Iot dashboard. It facilitates sorting the data entries in ascending and descending order. This sorting can be done by both horizontal rows and vertical columns of the pivot table for effective indoor positioning data analytics for the best RTLS asset tracking systems in manufacturing

Sample RTLS Analytics data

Indoor Location Data Analytics

RipplesIPS Indoor positioning system provides the industrial capability for deployment to scale when it comes to large areas. Indoor positioning system research paper on request for verticals such as healthcare, logistics, manufacturing & construction industries. Use the Pivotal table to identify warehouse choke points.

Q: How does indoor positioning analytics improve warehouse productivity? A: By analysing indoor positioning data, managers can identify “bottlenecks” in forklift movement and pallet ageing. Our Warehouse Tracking System uses these analytics to optimise travel paths, reducing fuel costs and labour hours.

Q: Can I integrate indoor analytics with my existing CMMS or ERP? A: Yes. Our RTLS solutions feature an open-source API for seamless integration with WMS, YMS and ERP platforms. This allows you to sync inventory management schedules for FiFo and LiFo operations.

Q: What is a “Movement Matrix” in RTLS? A: A movement matrix is a data visualisation that shows the frequency and duration of movement between specific zones. In a manufacturing shop floor, this helps in reconfiguring layout designs to minimise unnecessary worker travel and improve workplace safety.

Call us to know more – How does the indoor positioning analytics work? How to implement shop floor data analytics solutions to improve factory and warehouse productivity from focused indoor positioning system companies.