def apidata_getdata():
if request.method == 'POST' or request.method == 'GET':
try:
#jsonc.data_to_json(
data = {
'chart_data':
json.loads(
jsonc.data_to_json(dynamodb.get_data_from_dynamodb())),
'title':
"IOT Data"
}
#data = data.replace("\"","'")
print("before json loads")
global counter
global result_df
# Convert to dataframe, dropping dynamoDB id column
df = pd.DataFrame(data['chart_data'], dtype=float).drop(
['id', 'speedkmhour', 'datetime_value'], axis=1)
result_df = ml.predict_danger(df)
print('RESULT DF')
print(result_df)
#dataj = json.loads(data)
print()
print("after json loads")
#print(dataj)
#return data
return jsonify(data)
#return jsonify(data)
except:
import sys
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def get_numofbid_and_maxspeed(datetimestart_value):
try:
data = []
dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('GrabDataTable')
numofbid = len(getListofBIDforLatestDTS())
data.append(numofbid)
response = table.query(
KeyConditionExpression=Key('device_id').eq('deviceid_zhiyang'),
ProjectionExpression='speedkmhour, bookingid',
FilterExpression=Key('datetimestart_value').eq(
datetimestart_value))
maxspeedlist = response['Items']
maxspeedlist = jsonc.data_to_json(maxspeedlist)
maxspeed = 0.0
bidWithMaxSpeed = ''
for i in json.loads(maxspeedlist):
currentspeed = i.get('speedkmhour')
if currentspeed > maxspeed:
maxspeed = currentspeed
bidWithMaxSpeed = i.get('bookingid')
data.append(round(maxspeed, 2))
data.append(bidWithMaxSpeed)
return data
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getIndivividualDashboard(bookingid):
try:
data = []
dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('GrabDataTable')
response = table.query(
KeyConditionExpression=Key('device_id').eq("deviceid_zhiyang"),
ProjectionExpression='speedkmhour',
FilterExpression=Key('bookingid').eq(bookingid))
items = jsonc.data_to_json(response['Items'])
numofrows = response['Count']
totalSpeed = 0.0
highestSpeed = 0.0
for i in json.loads(items):
speed = i.get('speedkmhour')
if speed > highestSpeed:
highestSpeed = speed
totalSpeed += speed
avgspeed = totalSpeed / numofrows
data.append(avgspeed)
data.append(highestSpeed)
data.append(numofrows)
return data
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getSummaryTable():
try:
data = dynamodb.getSummaryTableData()
return jsonify(json.loads(jsonc.data_to_json(data)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getdata():
if request.method == 'POST' or request.method == 'GET':
try:
#jsonc.data_to_json(
data = {
'chart_data':
json.loads(
jsonc.data_to_json(dynamodb.get_data_from_dynamodb())),
'title':
"IOT Data"
}
#data = data.replace("\"","'")
print("before json loads")
print(data)
#dataj = json.loads(data)
print()
print("after json loads")
#print(dataj)
#return data
return jsonify(data)
#return jsonify(data)
except:
import sys
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getBooking(bid):
try:
dataRows = dynamodb.getindividualBookingData(bid)
return jsonify(json.loads(jsonc.data_to_json(dataRows)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getDriverSpeedingDetails():
try:
driversImages = dynamodb.getLatest3DriversthatSped()
return jsonify(json.loads(jsonc.data_to_json(driversImages)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getIndividualMapData(bid):
try:
bookingid = bid
mapdata = dynamodb.getIndividualMapData(bookingid)
return jsonify(json.loads(jsonc.data_to_json(mapdata)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getIndividualSpeedDetails(bid):
try:
bookingid = bid
data = dynamodb.getIndivividualDashboard(bookingid)
return jsonify(json.loads(jsonc.data_to_json(data)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getdata3():
if request.method == 'POST' or request.method == 'GET':
try:
data = {'chart_data': jsonc.data_to_json(dynamodb3.get_data_from_dynamodb()), 'title': "IOT Data"}
return jsonify(data)
except:
import sys
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def api_getChartData():
if request.method == 'POST':
try:
data = jsonc.data_to_json(dynamodb.get_chart_data())
loaded_data = jsonc.json.loads(data)
# print(loaded_data)
return jsonify(loaded_data)
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
return None
def checkLatestImage(bid):
try:
bookingid = bid
data = []
image, facesimilarity, ageDetails = dynamodb.retrieveImageFromS3forIndex(
bookingid)
data = [image, facesimilarity, ageDetails]
return jsonify(json.loads(jsonc.data_to_json(data)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getTotalNumOfVehicles():
try:
datarows = []
maxdatetimestart = dynamodb.get_maxdatetimestart_from_dynamodb()
datarows.append(dynamodb.get_numofbid_and_maxspeed(maxdatetimestart))
datarows.append(
dynamodb.getDistinctBidandAvgSpeedandCount(maxdatetimestart))
return jsonify(json.loads(jsonc.data_to_json(datarows)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getMapData():
try:
data = []
maxdatetimestart = dynamodb.get_maxdatetimestart_from_dynamodb()
listofBID = dynamodb.getListofBIDforLatestDTS()
for bid in listofBID:
data.append(dynamodb.getMapData(bid, maxdatetimestart))
return jsonify(json.loads(jsonc.data_to_json(data)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getdata():
try:
maxdatetimestart = dynamodb.get_maxdatetimestart_from_dynamodb()
data_reversed = dynamodb.get_top10data_from_dynamodb(maxdatetimestart)
datarows = jsonc.data_to_json(data_reversed)
#return data_reversed'''
return jsonify(json.loads(datarows))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getdata():
if request.method == 'POST' or request.method == 'GET':
try:
all_unique = dynamodb.get_all_unique()
daily_unique_rfid = dynamodb.get_daily_urfid_dynamodb()
data = {
'ambient_data':
jsonc.data_to_json(dynamodb.get_data_from_dynamodb()),
'human_data':
len(daily_unique_rfid)
}
counter = 1
for i in all_unique:
emp_data = jsonc.data_to_json(dynamodb.fetch_past_rfid(i))
#wott = 'emp_data' + str(counter)
data[i] = emp_data
#counter = counter + 1
return jsonify(data)
except:
import sys
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def status():
try:
data = jsonc.data_to_json(dynamodb.get_status())
loaded_data = jsonc.json.loads(data)
# print(loaded_data)
return jsonify(loaded_data)
status = loaded_data[0].status
return status
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
return None
def apidata_getdata():
if request.method == 'POST':
try:
data = {
'chart_data':
jsonc.data_to_json(dynamodb.get_data_from_dynamodb()),
'lightnow': real_time(),
'title': "IOT Data"
}
print(data)
return jsonify(data)
except:
print("apidata_getdata error")
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def captureDriverImage(bid):
try:
bookingid = bid
cam = cv2.VideoCapture("http://27.104.173.113:8081/out.jpg")
ret, frame = cam.read()
if not ret:
exit()
currentdatetime = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
imgpathaddon = currentdatetime.replace(":", ".")
imgpathaddon = imgpathaddon.replace(" ", "_") + ".jpg"
imgname = bookingid + "_" + imgpathaddon
success = dynamodb.uploadImageFileToS3(frame, imgname)
print(success)
#cv2.imwrite(imgname,frame)
print(imgname)
cam.release()
host = "a3kfg2bxlkhyhy-ats.iot.us-east-1.amazonaws.com"
rootCAPath = "certs/rootca.pem"
certificatePath = "certs/certificate.pem.crt"
privateKeyPath = "certs/private.pem.key"
my_rpi = AWSIoTMQTTClient("p1828430")
my_rpi.configureEndpoint(host, 8883)
my_rpi.configureCredentials(rootCAPath, privateKeyPath,
certificatePath)
my_rpi.configureOfflinePublishQueueing(
-1) # Infinite offline Publish queueing
my_rpi.configureDrainingFrequency(2) # Draining: 2 Hz
my_rpi.configureConnectDisconnectTimeout(10) # 10 sec
my_rpi.configureMQTTOperationTimeout(5) # 5 sec
# Connect and subscribe to AWS IoT
my_rpi.connect()
imageData = {
'VehicleType': 'GrabCar',
'datetime_value': currentdatetime,
'bookingid': bookingid,
'KeyName': imgname
}
my_rpi.publish("iotdatabase/image", json.dumps(imageData), 1)
return jsonify(json.loads(jsonc.data_to_json(success)))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getDistinctBidandAvgSpeedandCount(datetimestart_value):
try:
data = []
bidData = []
bidList = []
bidCounter = []
bidTotalSpeed = []
dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('GrabDataTable')
response = table.query(
KeyConditionExpression=Key('device_id').eq('deviceid_zhiyang'),
FilterExpression=Key('datetimestart_value').eq(
datetimestart_value),
ProjectionExpression='bookingid, speedkmhour')
items = response['Items']
items = jsonc.data_to_json(items)
for i in json.loads(items):
currentbid = i.get('bookingid')
currentbidspeed = i.get('speedkmhour')
if currentbid not in bidList:
bidList.append(currentbid)
bidCounter.append(1)
bidTotalSpeed.append(currentbidspeed)
else:
index = bidList.index(currentbid)
totalspeed = bidTotalSpeed[index]
bidTotalSpeed[index] = totalspeed + currentbidspeed
totalcount = bidCounter[index]
bidCounter[index] = totalcount + 1
for i in range(len(bidList)):
bidData = []
bidData.append(bidList[i])
totalspeed = bidTotalSpeed[i]
avgspeed = totalspeed / bidCounter[i]
bidData.append(round(avgspeed, 2))
bidData.append(bidCounter[i])
data.append(bidData)
return data
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getdata():
if request.method == 'POST' or request.method == 'GET':
try:
data = {
'chart_data':
jsonc.data_to_json(dynamodb.get_data_from_dynamodb()),
'title': "Visitor Data"
}
#print("TEMP DATA")
#print("***")
#print(jsonify(data))
#print("***")
return jsonify(data)
except:
import sys
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def apidata_getdata():
if request.method == 'POST' or request.method == 'GET':
try:
global timevalues
global oldSpeed
global client
my_bot_token = '1222581641:AAERMoml2QxBI_pYyLmmV2fdrm059rKSDps'
bot = telepot.Bot(my_bot_token)
limit = 1000
bookingid = "ALL"
if 'bookingid' in request.form:
bookingid = request.form['bookingid']
if 'datalimit' in request.form:
limit = request.form['datalimit']
loaded_r = json.loads(jsonc.data_to_json(get_data_from_dynamodb()))
loadedDict = loaded_r[-1]
bookingid = float(loadedDict.get('bookingid'))
accuracy = float(loadedDict.get('accuracy'))
bearing = float(loadedDict.get('bearing'))
acceleration_x = float(loadedDict.get('acceleration_x'))
acceleration_y = float(loadedDict.get('acceleration_y'))
acceleration_z = float(loadedDict.get('acceleration_z'))
gyro_x = float(loadedDict.get('gyro_x'))
gyro_y = float(loadedDict.get('gyro_y'))
gyro_z = float(loadedDict.get('gyro_z'))
seconds = float(loadedDict.get('seconds'))
speed = float(loadedDict.get('speed'))
testingBookingID = [[
bookingid, accuracy, bearing, acceleration_x, acceleration_y,
acceleration_z, gyro_x, gyro_y, gyro_z, seconds, speed
]]
loaded_model = pickle.load(open('iotModel', 'rb'))
df = pd.DataFrame(testingBookingID,
columns=[
'bookingid', 'accuracy', 'bearing',
'acceleration_x', 'acceleration_y',
'acceleration_z', 'gyro_x', 'gyro_y',
'gyro_z', 'seconds', 'speed'
])
predictedSafety = loaded_model.predict(df)
safetyValue = predictedSafety.item(0)
# dataSpeed = loaded_r["data"][-1]["speedkmhour"]
# dataBookingid = loaded_r["data"][-1]["bookingid"]
if safetyValue == 1:
returnStr = "You are going at %.3f for BookingID %s. Please slow down" % (
speed, bookingid)
print("Message has been sent!")
bot.sendMessage(324643817, returnStr)
if safetyValue == 1:
print("A bit fast there buddy")
print(safetyValue)
data = {'chart_data': loaded_r, 'title': "IOT Data"}
return data
except:
import sys
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def getSummaryTableData():
try:
data = []
datetimestartList = []
dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('GrabDataTable')
listofbid = getListofAllBID()
for bid in listofbid:
bidData = [bid]
response = table.query(
KeyConditionExpression=Key('device_id').eq('deviceid_zhiyang'),
ProjectionExpression=
'seconds, speedkmhour, datetime_value , datetimestart_value',
FilterExpression=Key('bookingid').eq(bid))
items = response['Items']
items = jsonc.data_to_json(items)
numofreadings = response['Count']
counter = 0
prevSpeed = 0.0
latestSpeed = 0.0
totalspeed = 0.0
totalduration = 0
latestdatetime = ''
speedingCounter = 0
datetimestartList = []
for i in json.loads(items):
counter += 1
totalduration += i.get('seconds')
speed = i.get('speedkmhour')
datetimestartvalue = i.get('datetimestart_value')
if datetimestartvalue not in datetimestartList:
datetimestartList.append(datetimestartvalue)
if speed > 90:
speedingCounter += 1
if counter == 1:
latestSpeed = speed
latestdatetime = i.get('datetime_value')
if counter == 2:
prevSpeed = speed
totalspeed += speed
avgspeed = totalspeed / numofreadings
bidData.append(totalduration)
bidData.append(len(datetimestartList))
bidData.append(avgspeed)
bidData.append(prevSpeed)
bidData.append(latestSpeed)
bidData.append(latestdatetime)
bidData.append(numofreadings)
bidData.append(speedingCounter)
data.append(bidData)
return data
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
def predictSafety(bid):
try:
# Obtain SQL Reading for selected BookingID (SQLQuery)
# https://www.kite.com/python/answers/how-to-convert-an-sql-query-result-to-a-pandas-dataframe-in-python
# https://stackoverflow.com/questions/12047193/how-to-convert-sql-query-result-to-pandas-data-structure
dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('modedata')
response = table.query(KeyConditionExpression=Key('bookingid').eq(bid))
datarows = response['Items']
df = pd.DataFrame(datarows, dtype=float)
#resoverall is yr sql statement
# df = DataFrame(resoverall.fetchall())
# df.columns = resoverall.keys()
df.drop(['accuracy'], axis=1, inplace=True)
df['acceleration'] = np.sqrt(
(df.loc[:, ('acceleration_x', 'acceleration_y',
'acceleration_z')]**2).sum(axis=1))
df.drop([
'acceleration_x', 'acceleration_y', 'acceleration_z', 'speedkmhour'
],
axis=1,
inplace=True)
pca_gyro = PCA(n_components=1).fit(
df.loc[:, ['gyro_x', 'gyro_y', 'gyro_z']])
df['gyro'] = pca_gyro.transform(df.loc[:,
('gyro_x', 'gyro_y', 'gyro_z')])
df.drop(['gyro_x', 'gyro_y', 'gyro_z'], axis=1, inplace=True)
data = pd.DataFrame()
for col in df.columns:
if col != "bookingid" and col != "label":
temp = df.groupby("bookingid")[col].agg(
["mean", "sum", "max", "min"])
data[col + "_mean"] = temp["mean"]
data[col + "_sum"] = temp["sum"]
data[col + "_max"] = temp["max"]
data[col + "_min"] = temp["min"]
#data = data.drop(columns=["bookingid"]).reset_index(drop=True)
data.drop(columns=["seconds_min"], inplace=True)
# generate distance, velocity and angle features
for col in data.columns:
if col.startswith("seconds"):
agg_method = col.split("_")[1]
data["distance_" +
agg_method] = data[col] * data["speed_" + agg_method]
data["velocity_" +
agg_method] = data[col] * data["acceleration_" +
agg_method]
data["angle_" +
agg_method] = data[col] * data["gyro_" + agg_method]
data = data.drop(columns=['seconds_sum', 'seconds_mean']).reset_index(
drop=True)
# Once Obtain model after hyper tuning save weights here and predict
from joblib import load
sr = load("GBR.joblib")
y_pred = sr.predict(data)
print("regression value: ", y_pred[0])
return jsonify(json.loads(jsonc.data_to_json(y_pred[0])))
except:
print(sys.exc_info()[0])
print(sys.exc_info()[1])
