Shop floor business intelligence
Indoor positioning systems. A dashboard can be defined as a graphical user interface that often provides at-a-glance views of key performance indicators (KPIs) relevant to a particular objective or business process. In another usage, ‘dashboard’ is a technical term for ‘progress report’ or ‘activity report’ and is considered a form of data visualization. Here’s a blog on how the dashboard is structured and the tools used for indoor positioning analytics. Gain new insights into warehouse tracking systems and hospital asset tracking systems.
Indoor positioning data analytics in warehouses & factories
Like warehouses, construction sites are the places where the maximum amount of deployments occur. The installation of the best Indoor Positioning System in such workplaces is a necessary thing for a smooth workflow. In the monitoring process of such deployments. Hardware components like beacons, tags, anchors play a crucial role, at the same time, the data signals collected by these components can be perceived only through software, called shopfloor. It is a central managing unit that acts as a dashboard, where a user can monitor, surveil, access, receive signals and analyze those signals in real-time using several data analytic tools. A user can monitor every signal from the sensors through the floor map. The data received from these sensors are collected and projected in the form of the pivot table. Indoor positioning solution companies are able to provide robust solutions which derive business intelligence to improve shop floor operations.
Indoor positioning analytics, impact of the choice
Construction site worker safety & security monitoring using the most accurate indoor positioning system
The choice of indoor positioning data analytics
- Virtual demarcation of a construction site into multiple
- Locating workers within respective zones created at the construction site
- Visualizing the location of these workers on a 2D map
- Mapping movement matrices of the workers to improve worker productivity and safety
- Features to analyze 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 time-spent reports of workers showing time spent by each worker in different zones at the site
- Generate reports showing the number of intrusions to restricted areas along with entry/exit time stamps
Indoor positioning systems & indoor location data analytics
The above requirements are available on the IOT Platform for construction site safety in the form of user-friendly features. These features were tested out by the research students at test facilities simulated within NUS (Singapore) which helped them gather various insights pertaining to a construction site.
This mainly involved capturing movement matrices of the workers, providing alerts when workers moved into restricted areas and providing time-spent reports of the workers in various zones of the simulated construction site. The insights gathered will be further used in real-world construction sites to ensure the improved safety of the workers. The same will also be used to educate concerned construction personnel on techniques to improve site efficiency and productivity.
Indoor positioning how to implement data analytics
The pivot table consists of fixed variables like date, zone, floor, object name, category, staff details in its rows, and changeable variables like name of the zones (OPD block, reception, exit way, etc), floors, 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 customization for representing those collected data. The data can be represented either or altogether in the following ways,
- Visual representation
- Quantitative representation
- Parameter to be represented
- Custom sorting based on zones, login, logout times
- Shopfloor elements drag and drop
- indoor positioning system arduino interface
Visual Representation of shopfloor data – The data received from the sensors are projected onto the pivot table through visual representation tools. It will be represented in the form of 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 are displayed on the pivot table as the numerical entries based on various parameters. These parameters can be selected based on needs. The parameters include time spent in a room, the temperature of a room, number of persons in a zone, number of visits paid 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 or an average of the visit counts, and so on.
Custom Sorting – This is a basic feature tool available in the activity report 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. The best indoor localization solutions for construction sites and warehouses.
Indoor positioning solution companies in India
indoor positioning system open source versions do not provide 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.
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