Optimizing energy expenses with IoT-driven asset monitoring
About the client
For decades the client has been counted among the world’s premium dairy businesses with a strong presence across the MENA region. It has sustained the position of a market leader in the Middle East, driven by years of creative policy-making, firm quality commitments, and innovation.
The company has an expansive business operation spanning several business facilities and campuses. Although it is a technology-driven and future-focused organization, the utility delivery systems across its facilities have been predominantly manual and left to the users’ whims. Consequently, employees leaving common areas with the lighting and air conditioning running were pilling massive electricity bills for the client. Therefore, it desired a solution that can remotely monitor and optimize the usage of lighting and HVAC systems across facilities, trimming OpEx.
The client was trying to cope with legacy electricity distribution systems installed across its business facilities that relied heavily on user habits and manual interventions. Often its employees left premises, forgetting to switch off the electrical systems. Consequently, the company was losing nearly $10 million to inefficient electricity usage every year. Additionally, apart from its environmental consequences, the cost of running the legacy energy distribution architecture led to various other complexities sinking over $300 million in aggregate for the organization.
The client decided to adopt a network-centric approach to tackling the nuisance and plugging these unacceptable revenue leakages. It was looking for an experienced technology partner for building a solution that can:
- Automatically notify technicians and maintenance staff whenever people leave the common areas during lean periods, without switching off the air conditioners, HVACs, or dimming the lights
- Constantly monitor the individual utility consumption across facilities and harness the usage data to optimize outcomes
A PiServe team of experts considered the client’s requests and thoroughly assessed the state of the electricity distribution architecture across facilities. It concluded that rather than appealing to the conscience of the employees, only an automated and intuitive solution that is constantly vigilant could deliver the desired results and save the organization millions of dollars in revenue.
The IoT technology holds enough scope to bring the required utility monitoring capabilities closer to the facility floors. Accordingly, as part of the engagement, the PiServe engineers:
Collaborated with the stakeholders on the client-side to propose and build an IoT device that can seamlessly interface with the electrical equipment and controllers on-site, ingesting a set of prioritized sensor data at a set frequency.
Designed and delivered an IoT platform to continuously log, monitor, and predict energy consumption patterns across the company’s facilities in the US, based on the historical data retrieved from various controllers. The platform can flag anomalies and trigger alarms for the responders whenever thresholds are breached.
IoT solution to effectively plug energy leakages and more responsive asset maintenance schedule by continuously monitoring HVAC and lighting systems across facilities and deploying maintenance teams on-site without delay.
Within months of implementation, the PiServe solution started delivering measurable and positive outcomes for the client. They have been instrumental in closely aligning the utility consumption patterns across the client’s facilities with the periodic fluctuation in demands. The benefits of adopting the customized device and IoT platform has been far-reaching, including:
Incurred an almost instant savings of $2 million for the organization from reduced energy expenses and system optimizations
Reduced cycle time
Lead time for an automated work-order generation was brought down from 36 hours to merely 4 hours
73% of field service work orders have been automated, eliminating the need for manual intervention
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