IoT Projects

Asset Monitoring and Predictive Maintenance

Problem: Reduce energy consumption at waste processing centres and reduce downtime of equipment through intelligent maintenance schedules.

Solution: Monitor motor temperature, speed, power consumption for extraction fans at waste processing facilities as well as fluid level monitoring trade waste pits – optimize operating times using data-based automation.

Outcomes: Reduction in energy consumption and cost, less downtime and ongoing maintenance costs

Oil & Gas Leak Detection

Problem: Cost of cleaning salt water due to pipeline leaks is astronomical (10 x more than oil). Current detection methods highly inaccurate due to false positives. Software can’t handle the volume of real-time data.

Solution: enables the collection real-time flow and pressure data of assets, creating alerts based on custom-built predictive algorithms.

Outcomes: Early detection of leaks reducing environmental damage and eliminating cleanup costs.

Smart Building management

Problem: Reduce cost of building maintenance. Ensure environmental compliance. Identify opportunities to improve utilisation.

Solution: enables the real-time collection of data at the room level across multiple floors and buildings and brings the data into one place. Alerts are raise when issues occur.

Outcomes: :Increase utilisation, reduce maintenance costs, ensure consistent and compliant working conditions.

Bridge Structural Health Monitoring

Problem: Deterioration of cables and anchorages, loss of paint and spalling of steel, scouring of piers and piles, and malfunction of bearings and expansion joints undermines the structural integrity of bridges and can lead to catastrophic failure.

Solution: Utilise advanced monitoring and predictive analytics of bridge structures and operating conditions in order to ensure timely and cost-effective bridge maintenance.

Outcomes: Increase in operating safety. Reduction in maintenance costs.

Energy Efficiency

Problem: No visibility to energy consumed beyond the whole-of-factory level. Concern that energy was being used inefficiently.

Solution: Deployed 3-phase Zigbee Schneider energy meters (2000A, Rogowski) at extruder switchboard. Used a RS232 to WiFi converter to transmit production data to the cloud.

Outcomes: Established first real-time view of energy data at a machine level; first view of energy+production data; first view of giveaway. Identified ~2 tonnes of giveaway per week. Moved startup spikes to low cost times of day.

Manufacturing Efficiency

Problem: Improve performance (throughput, product quality) while reducing operational costs.

Solution: Collect data from existing systems (ERP, SCADA, PLCs) combined with new data from meters and sensors to identify new insights and opportunities for improvement.

Outcomes: Reduction in energy consumption, reduction in production waste, predictive maintenance, OEE increase.

Fleet Management, Maintenance and Safety

Problem: Inefficient use of trucks, poor driver safety, costly maintenance schedules.

Solution: Use CANbus data to monitor efficiency, to create models of driver safety and to predict when trucks need servicing.

Outcomes: :Improved driver safety records, decreased spending on fuel and maintenance. Increase in truck utilization rates. Improved customer experience.

Supply Chain Optimisation

Problem: Customer demands for increased efficiency, compliance and accountability on logistics and supply chain companies means increase costs.

Solution: enables the collection real-time location, weight and vibration data as well as enabling predictive pallet utilisation analytics.

Outcomes: Improved living conditions and response times for patients. Improved confidence and trust between families and care providers. Improved compliance with healthcare regulations.

In-Home Monitoring

Problem: Poor conditions and sub-par treatment of the elderly and mentally impaired in nursing homes and public health facilities.

Solution: enables in-home real-time monitoring of the physical environment to ensure the wellbeing and comfort of patients and timely response of carers. Includes real-time alerts and predictive analytics.

Outcomes: Improved living conditions and response times for patients. Improved confidence and trust between families and care providers. Improved compliance with healthcare regulations.

Retail Efficiency and Predictability

Problem: Poor performing stores, loss of revenue when not able to meet demand during peak periods.

Solution: Measure foot traffic, combined with seasonal trending and real-time sales data to predict times of high demand, inventory requirements and to monitor store performance (conversion rates, average basket size, daily performance etc.)

Outcomes: Identify poor performing stores by location or time period quickly so early intervention can be taken to increase revenue and profitability.