SenseGrow Case Studies Medanta the Medicity
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Medanta the Medicity

SenseGrow
Medanta the Medicity - SenseGrow Industrial IoT Case Study
Platform as a Service (PaaS) - Data Management Platforms
Healthcare & Hospitals
Facility Management
Building Automation & Control
Medanta is one of India's largest multi-super specialty institutes located in Gurgaon, India. Some of the key challenges facing Medanta included:
- No Monitoring & Control over Energy Use, Indoor Air Quality, Indoor Lighting Quality & Noise Levels.
- No compliance monitoring of temperature & pressure in critical care wards.
- Energy bills were a surprise with no way to forecast energy costs.
- Missing data & insights that could be used for targeting areas of improvement.
- Existing Billing Management System (BMS) was inflexible and could not be used across the enterprise to serve the needs of different users.

Requirements
Based on these challenges, Medanta was looking for a comprehensive solution to Monitor & Control:
- Energy Usage
- Power Generators
- Clean Rooms
- HVAC Temperature
- Chiller Temperature
- Hydrant Pressure
- Air Quality & Noise Levels
- Critical Wards
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Medanta is one of India's largest multi-super specialty institutes located in Gurgaon, India. Medanta is governed under the guiding principles of providing medical services to patients with care, compassion and commitment. Spread across 43 acres, the inst
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Medanta
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SenseGrow worked with our partner, LogicLadderTM, to deliver a comprehensive solution. Devices from multiple vendors would connect with ioEYETM. This data is then made available to EnergyLogicIQTM in a manner that enables them to access these devices without knowing the underlying technologies.

Using ioEYE’s Reports, Dashboards and Smart Alerts, EnergyLogicIQ is able to run analytics on this data to provide actionable insights.
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[Data Management - Data Integration]
Today, Medanta is a smart IoT enabled green campus where people and things collaborate for greater business success.
[Data Management - Real Time Data]
Different stakeholders are aware of what is happening in real-time, and have insights for better collaboration between teams.
[Cost Reduction - Maintenance]
Advanced analytics and machine learning provide information that let them identify anomalies, act in time and take corrective actions for efficient use of assets - lowering operation, energy and maintenance costs.
11% overall reduction in Energy consumption
100% compliance of temperature & pressure monitoring in critical care units and wards
3% overall reduction in fuel expenses. 100% vigil on fuel theft in diesel generators
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