IOTFOG based Smart recommender system for efficient water utilization
with the assistance of IoT, ML, and hybrid architecture, we will propose a water recommender system for a smart efficient water utilization framework. Our proposed recommender system will be able to measure and monitor the consumption of water. Moreover, we will use
2025-06-28 16:28:24 - Adil Khan
IOTFOG based Smart recommender system for efficient water utilization
Project Area of Specialization Information & Communication TechnologyProject Summarywith the assistance of IoT, ML, and hybrid architecture, we will propose a water recommendersystem for a smart efficient water utilization framework. Our proposed recommender system will be able to measure and monitor the consumption of water. Moreover, we will use multiple sensors for developing a smart water recommender proper dataset. Another objective of our proposed recommender system will provide timely recommendations such as in case of water shortage during drought and low pressure during hours of peak demand. To conclude, our proposed recommender system will provide efficient water utilization and promote water consumption behavior household consumers.
Project Objectives- To develop and design ML-IOT based Smart water utilization and recommendation mechanism especially for a household.
- To deploy the proposed prototype in a control environment.
- To design a communication stack for the proposed idea
- To set up a communication mechanism with the cloud and Fog computing model for efficient energy utilization.
In this project, our ?smart recommender system will help us to measure and monitor the consumption of water. We will attach different types of sensors on our smart taps . These sensors will help us to measure water consumption. After taking readings from the sensors, we will execute feature prioritization algorithm by using Raspberry pi (EDGE node) , Fog node and cloud services. Then, we will make our IoHT dataset and save it on the cloud server (AWS). We will use a wireless network for transferring data from IoT to the cloud. By taking advantage of Fog Computing, we will save data ofconsumption of water on cloud services. Then we will use different machine learning classifiers that help us in predicting and develop recommendations foor users. Furthermore, a mobile application will be used to display the details of consuming the water by users, so that we can see what prediction is made by our smart system.
Benefits of the ProjectThe fundamental benefit behind our idea is to encourage water consumption behaviour among consumers. Moreover, it helps to recommend user weather he/she can conume more water or not. Furthermore, it can also monitor water utilization. Another objective of our proposed recommender system will provide timely recommendations such as in case of water shortage during drought and low pressure during hours of peak demand.
Technical Details of Final Deliverable
In Deilverable 1: Thingspeak is collecting data from the three taps which use IOT protocols. Thingspeak aggregate and analyze data in the cloud. Data is then further sent for processing from which required data is sent for data prioritization.
In Deliverable 2: there are three platforms to save the data. After Data is prioritized it is sent to hybrid computing in cloud, fog, or edge according to the requirement. In the computing process, data is analyzed recommendations are generated.
in Deliverable 3: a recommendation process that acquires recommendations and the action is performed and displayed in the mobile application.
Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Others Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 57520 | |||
| Raspberry pie 4B (2GB) | Equipment | 2 | 15000 | 30000 |
| Water Flow senser | Equipment | 4 | 500 | 2000 |
| RASPBERRY pie 4case | Miscellaneous | 2 | 450 | 900 |
| Vertical Mount float switch for water level sensing | Equipment | 1 | 300 | 300 |
| Micro server motor | Equipment | 4 | 550 | 2200 |
| Arduino UNO | Equipment | 4 | 700 | 2800 |
| Arduino cable | Miscellaneous | 3 | 150 | 450 |
| Raspberry pi power adopter | Equipment | 2 | 600 | 1200 |
| Sd card (32 GB) | Miscellaneous | 2 | 1500 | 3000 |
| PCB fabrication | Miscellaneous | 5 | 300 | 1500 |
| Buzzer / LED's/ resistors / buttons | Miscellaneous | 1 | 500 | 500 |
| Batteries (5 V, 3A) | Equipment | 5 | 1000 | 5000 |
| Node MCU | Equipment | 5 | 800 | 4000 |
| jumper vires | Miscellaneous | 10 | 150 | 1500 |
| vero Board | Equipment | 6 | 70 | 420 |
| IR senser | Equipment | 5 | 200 | 1000 |
| Motion senser | Equipment | 4 | 150 | 600 |
| BreadBoard | Equipment | 1 | 150 | 150 |