*********Read Me****

The data collection includes data from 5th July to 5th December 2015.

1) Aggregated_data: includes the aggregated data of the household.

2) Appliance_data: includes all the appliance level data collected in the household. 

3) All_data: includes both aggregated (mains) and appliance level data.

4) DRED.h5: includes the H5 format file for NILMTK import.

5) BT_rssi.csv: includes the BT beacon RSSI values sensed every 1 minute by the occupant's mobile phone. The details include Time,Id,RSSI,Temperature,BatteryLevel,Proximity,Location.

6) WiFI_RSSI.csv:  includes the WIFI access points RSSI values sensed every 1 minute by the occupant's mobile phone. Will be updated soon.

7) Temperature.csv: includes the indoor (room-level) temperature and outdoor temperature.

8) dred_nilmtk.py: sample NILMTK code to import DRED dataset for energy disaggregation. 

9) Occupancy_data.csv: Partial occupancy data inferred using RSSI based localization mechanisms. These are accurate locations of users when an application was used.

10) Fingerprint_data: includes room level WiFi and BT RSSI data for fingerprinting. This can be used for localization algorithms.


To obtain location information every 1 min:

1. Please use the BT_rssi.csv file along with fingerprint data with you favourite classifier(Bayesian, KNN) to derive room-level location information.

2. Soon we shall provide our classifier code and the minute level inferred locations.

Bluetooth Beacon placement:
	Room 1:   'beacon_69', 'beacon_27'
	Room 2:   'beacon_92', 'beacon_87'
Living Room:  'beacon_17', 'beacon_79', 'beacon_75'
	Kitchen:  'beacon_3E', 'beacon_0D', 'beacon_8C'
Store Room:   'beacon_40', 'beacon_50'
	Outside:  'beacon_06'