Indium Software’s IIoT Analytics services help enhance manufacturing and industrial processes, which is a main component of Industry 4.0. We have deployed IIoT services across domains like manufacturing, consumer wearables, smart homes, smart electronics, automotive, telematics, weather forecasting etc.
IoT Analytics Service Offerings
- IoT Data Ingestion into a platform (Data Warehouse or Data Lake depending on data volume)
- Data Streaming & Refresh – Real-time or Near Real-time
- Data Processing – Loading, Cleansing, Transformation & Aggregation
- Build Analytical Models based on Machine Learning
- Create Visualization & Consumption Layers – Reports/Dashboards & Applications/Portals
Benefits of our IoT Analytics as a Service
Customer experience optimization
Predictive care, Safety analytics, queue minimization and more
Product performance optimization
Traffic management, Predictive maintenance, Smart grid analytics and more
People process optimization
Smart assistance, Driver behavior modification, Route optimization and more
Energy utilization analytics, Infrastructure optimization, fuel consumption analytics and more
IoT Analytics Solutions from Indium
Indium’s IoT Analytics Process
We take care of the hurdles in the IoT analytics solutions implementation to allow your business to benefit from IoT insights at a macro level. We leverage our analytics expertise to take over the analytics bound tasks. Here is how we put our IoT analytics services into action:
Checking for IoT readiness
Firstly, we assess your business goals and the level of analytics maturity that is existent. Based on the information gleaned, relevant analytics methods are chosen keeping in mind the feasibility and the possibility to improve strategic decision making. A detailed report with monitoring procedures, ascertained KPIs, SLAs and document service timings will be provided.
Data quality assessment and data preparation
We analyze the available IoT data and metadata from various perspectives such as quality and structure to check for consistency, accuracy, completeness and auditability. This is done to check the analytics readiness. Our big data engineers ensure accuracy of the IoT analytics results by cleansing and reorganizing data that is erroneous, incomplete or has duplicate values.
We use diagnostic, descriptive, predictive and prescriptive analytics to detect hidden trends and dependencies in historical and streaming data to make predictions based on them. Our IoT analytics services also uncover root causes of past events. The insights gained through our analytics are presented via:
Ad hoc reports: This helps drill down on any parameter and allow for custom reports to be built on the fly.
Alerts: These alerts are based on predefined rules and are generated automatically.
Standard reports: A predefined range of parameters are set, on which insights are provided at regular intervals data preparation
IoT Analytics Use cases
For a large SE Asian Taxi player, with a fleet size of about 23,000 spread over 61 depots, we leveraged Geospatial analytics using the Haversine formula to calculate distance between two points and divide the city into grids thereby increasing occupancy rates.
Helped an Energy Consulting Company detect faulty wind turbines using the wind turbine sensor data transmitted with the help of Survival analysis and classification techniques like kNN, Neural Networks.