def __init__(self, value_json): #init variable self.last_gateway_sum = {} #float(os.environ['last_gateway_sum']) self.last_gateway_count = {} #float(os.environ['last_gateway_count']) self.gateway = {} self.gateway_sum = {} self.gateway_count = {} self.tag_kal = {} #float(os.environ['tag_kal']) self.pathloss_kal = {} #float(os.environ['pathloss_kal']) for datas in value_json['Gateway']['value']: data = value_json['Gateway']['value'][datas] self.gateway[data['Mac']] = data['last'] self.gateway_sum[data['Mac']] = data['sum'] self.gateway_count[data['Mac']] = data['count'] self.last_gateway_sum[data['Mac']] = data['sum'][4] self.last_gateway_count[data['Mac']] = data['count'][4] for datas in value_json['Tag']['value']: data = value_json['Tag']['value'][datas] self.tag_kal[data['Mac']] = data['Last_kal'] for datas in value_json['Pathloss']['value']: data = value_json['Pathloss']['value'][datas] self.pathloss_kal[data['Mac']] = data['Last_kal'] #init estimate P = value_json['kalman']['P'] K = value_json['kalman']['K'] Q = value_json['kalman']['Q'] R = value_json['kalman']['R'] self.est = estimate_dis(P, K, Q, R)
def __init__(self, value_json): #init variable self.last_gateway_sum = {} #float(os.environ['last_gateway_sum']) self.last_gateway_count = {} #float(os.environ['last_gateway_count']) self.gateway = {} self.gateway_sum = {} self.gateway_count = {} ##begin test adjust rssi ## self.adjust = {} self.adjust['ac:23:3f:a2:16:59'] = 2 self.adjust['ac:23:3f:a2:16:93'] = 0 self.adjust['ac:23:3f:a2:16:c2'] = -3 self.adjust['ac:23:3f:a2:16:c0'] = 1 ## ##end test adjust rssi self.location = {} self.tag_kal = {} #float(os.environ['tag_kal']) self.pathloss_kal = {} #float(os.environ['pathloss_kal']) self.dis_pathloss = {} self.dis_tag = {} self.delta = value_json['Delta'].copy() for gateway in value_json['Gateway']: for datas in gateway['value']: data = gateway['value'][datas].copy() self.gateway[data['Mac']] = data['last'] self.gateway_sum[data['Mac']] = data['sum'] self.gateway_count[data['Mac']] = data['count'] self.last_gateway_sum[data['Mac']] = data['sum'][4] self.last_gateway_count[data['Mac']] = data['count'][4] for datas in value_json['Tag']['value']: data = value_json['Tag']['value'][datas].copy() self.tag_kal[data['Mac']] = data['Last_kal'] self.dis_tag[data['Mac']] = 0 for pathloss in value_json['Pathloss']: for datas in pathloss['value']: data = pathloss['value'][datas].copy() self.pathloss_kal[data['Mac']] = data['Last_kal'] self.location[data['Mac']] = data['location'] self.dis_pathloss[data['Mac']] = self.calculate_path_dis( data['location'], pathloss['location']) #init estimate P = value_json['kalman']['P'] K = value_json['kalman']['K'] Q = value_json['kalman']['Q'] R = value_json['kalman']['R'] self.est = estimate_dis(P, K, Q, R) self.rssi1m = value_json['kalman']['RSSI1m']
def __init__(self, value_json): #init variable self.last_gateway_sum = {} #float(os.environ['last_gateway_sum']) self.last_gateway_count = {} #float(os.environ['last_gateway_count']) self.gateway = {} self.gateway_sum = {} self.gateway_count = {} self.location = {} self.tag_kal = {} #float(os.environ['tag_kal']) self.pathloss_kal = {} #float(os.environ['pathloss_kal']) self.dis_pathloss = {} self.dis_tag = {} self.delta = value_json['Delta'].copy() for gateway in value_json['Gateway']: for datas in gateway['value']: data = gateway['value'][datas].copy() self.gateway[data['Mac']] = data['last'] self.gateway_sum[data['Mac']] = data['sum'] self.gateway_count[data['Mac']] = data['count'] self.last_gateway_sum[data['Mac']] = data['sum'][4] self.last_gateway_count[data['Mac']] = data['count'][4] for datas in value_json['Tag']['value']: data = value_json['Tag']['value'][datas].copy() self.tag_kal[data['Mac']] = data['Last_kal'] self.dis_tag[data['Mac']] = 0 for pathloss in value_json['Pathloss']: for datas in pathloss['value']: data = pathloss['value'][datas].copy() self.pathloss_kal[data['Mac']] = data['Last_kal'] self.location[data['Mac']] = data['location'] self.dis_pathloss[data['Mac']] = self.calculate_path_dis( data['location'], pathloss['location']) #init estimate P = value_json['kalman']['P'] K = value_json['kalman']['K'] Q = value_json['kalman']['Q'] R = value_json['kalman']['R'] self.est = estimate_dis(P, K, Q, R)
def __init__(self, value_json): #init variable self.last_gateway_sum = {} #float(os.environ['last_gateway_sum']) self.last_gateway_count = {} #float(os.environ['last_gateway_count']) self.check_none = 1 self.check_enough = 0 self.gateway = {} self.gateway_sum = {} self.gateway_count = {} #2020.04.09 #self.calib=[-53.66,-49.05,-49.38,-48.27,-48.16,-47.13,-48.66,-48.08,-47.23,-47.01,-50.23,-49.68,-49.77,-50.09,-50.27,-53.15,-53.55,-50.71,-50.44,-51.03,-51.35,-53.04,-54.29,-57.70,-59.09,-61.35,-56.310,-62.53,-63.99,-61.23,-57.24,-54.44,-54.94,-54.12,-53.980,-53.780,-53.66] #2020.04.10 #self.calib=[-53.66,-54.22,-50.87,-49.13,-49.000,-49.20,-50.61,-50.47,-53.21,-52.29,-53.13,-56.51,-58.53,-60.72,-59.02,-57.52,-55.22,-53.60,-50.44,-51.03,-51.35,-53.04,-54.29,-57.70,-59.09,-61.35,-56.310,-62.53,-63.99,-61.23,-57.24,-54.44,-54.94,-54.12,-53.980,-53.780,-53.66] #2020.04.14 self.calib = [ -53.66, -51.92, -52.58, -52.82, -52.00, -50.86, -49.33, -48.84, -48.68, -49.74, -49.26, -51.72, -51.60, -52.42, -52.78, -52.70, -54.15, -53.41, -50.44, -51.03, -51.35, -53.04, -54.29, -57.70, -59.09, -61.35, -56.310, -62.53, -63.99, -61.23, -57.24, -54.44, -54.94, -54.12, -53.980, -53.780, -53.66 ] ##begin test adjust rssi ## self.adjust = {} #self.adjust['ac:23:3f:a2:16:59']=3.1251703178650487 #self.adjust['ac:23:3f:a2:16:93']=-1.3577211252097143 #self.adjust['ac:23:3f:a2:16:c2']=-0.47533575755330304 #self.adjust['ac:23:3f:a2:16:c0']=1.1714324033986117 ## ##end test adjust rssi ##begin hard set angle beacon ## self.angle_beacon = {} self.angle_beacon['ac:23:3f:a2:16:59'] = 90 self.angle_beacon['ac:23:3f:a2:16:93'] = 180 self.angle_beacon['ac:23:3f:a2:16:c2'] = 180 self.angle_beacon['ac:23:3f:a2:16:c0'] = 270 self.location = {} self.tag_kal = {} #float(os.environ['tag_kal']) self.pathloss_kal = {} #float(os.environ['pathloss_kal']) self.dis_pathloss = {} self.dis_tag = {} self.location_pathloss = {} self.beacon = [] self.last_tag_location = None self.delta = value_json['Delta'].copy() for gateway in value_json['Gateway']: for datas in gateway['value']: data = gateway['value'][datas].copy() self.gateway[data['Mac']] = data['last'] self.gateway_sum[data['Mac']] = data['sum'] self.gateway_count[data['Mac']] = data['count'] self.last_gateway_sum[data['Mac']] = data['sum'][4] self.last_gateway_count[data['Mac']] = data['count'][4] if data['count'][4] > 2000: self.check_enough = 1 for datas in value_json['Tag']['value']: data = value_json['Tag']['value'][datas].copy() self.tag_kal[data['Mac']] = data['Last_kal'] self.dis_tag[data['Mac']] = 0 if not (value_json['Tag']['location'] is None): self.last_tag_location = value_json['Tag']['location'].copy() self.check_none = 0 for pathloss in value_json['Pathloss']: self.location_pathloss = pathloss['location'].copy() for datas in pathloss['value']: data = pathloss['value'][datas].copy() self.adjust[data['Mac']] = 0 self.pathloss_kal[data['Mac']] = data['Last_kal'] self.location[data['Mac']] = data['location'] self.dis_pathloss[data['Mac']] = self.calculate_path_dis( data['location'], pathloss['location']) #init estimate P = value_json['kalman']['P'] K = value_json['kalman']['K'] Q = value_json['kalman']['Q'] R = value_json['kalman']['R'] self.est = estimate_dis(P, K, Q, R) self.rssi1m = value_json['kalman']['RSSI1m'] self.Recalculate_Adjust(self.last_tag_location, self.location_pathloss, self.location, self.angle_beacon)
def __init__(self, value_json): #init variable self.last_gateway_sum = {} #float(os.environ['last_gateway_sum']) self.last_gateway_count = {} #float(os.environ['last_gateway_count']) self.check_none = 1 self.check_enough = 0 self.gateway_kal = {} self.last_gateway_kal = {} self.gateway = {} self.gateway_sum = {} self.gateway_count = {} #2020.04.09 #self.calib=[-53.66,-49.05,-49.38,-48.27,-48.16,-47.13,-48.66,-48.08,-47.23,-47.01,-50.23,-49.68,-49.77,-50.09,-50.27,-53.15,-53.55,-50.71,-50.44,-51.03,-51.35,-53.04,-54.29,-57.70,-59.09,-61.35,-56.310,-62.53,-63.99,-61.23,-57.24,-54.44,-54.94,-54.12,-53.980,-53.780,-53.66] #2020.04.10 #self.calib=[-53.66,-54.22,-50.87,-49.13,-49.00,-49.20,-50.61,-50.47,-53.21,-52.29,-53.13,-56.51,-58.53,-60.72,-59.02,-57.52,-55.22,-53.60,-50.44,-51.03,-51.35,-53.04,-54.29,-57.70,-59.09,-61.35,-56.310,-62.53,-63.99,-61.23,-57.24,-54.44,-54.94,-54.12,-53.980,-53.780,-53.66] #2020.04.14=[-00.10,-00.20,-00.30,-00.40,-00.50,-00.60,-00.70,-00.80,-00.90,-01.00,-01.10,-01.20,-01.30,-01.40,-01.50,-01.60,-01.70,-01.80 self.calib = [ -43.24, -42.75, -42.66, -42.59, -42.72, -43.29, -44.07, -44.39, -46.08, -49.23, -55.39, -54.95, -56.89, -56.68, -51.45, -48.19, -46.31, -46.27, -47.70, -51.03, -51.35, -53.04, -54.29, -57.70, -59.09, -61.35, -56.310, -62.53, -63.99, -61.23, -57.24, -54.44, -54.94, -54.12, -53.980, -53.780, -53.66 ] #self.calib= [-43.24,-42.75,-42.66,-42.59,-42.72,-43.29,-44.07,-45.39,-49.23,-48.06,-55.39,-54.95,-56.89,-56.68,-51.45,-48.19,-46.31,-46.27,-47.70,-51.03,-51.35,-53.04,-54.29,-57.70,-59.09,-61.35,-56.310,-62.53,-63.99,-61.23,-57.24,-54.44,-54.94,-54.12,-53.980,-53.780,-53.66] ##begin test adjust rssi ## #self.adj={} self.adjust = {} #self.adj['ac:23:3f:a2:16:59']=0.029 #self.adj['ac:23:3f:a2:16:93']=0 #self.adj['ac:23:3f:a2:16:c2']=-3.476 #self.adj['ac:23:3f:a2:16:c0']=0 ## ##end test adjust rssi ##begin hard set angle beacon ## self.angle_beacon = {} self.angle_beacon['ac:23:3f:a2:16:59'] = 110 self.angle_beacon['ac:23:3f:a2:16:93'] = 185 self.angle_beacon['ac:23:3f:a2:16:c2'] = 195 self.angle_beacon['ac:23:3f:a2:16:c0'] = 280 self.location = {} self.tag_kal = {} #float(os.environ['tag_kal']) self.pathloss_kal = {} #float(os.environ['pathloss_kal']) self.dis_pathloss = {} self.dis_tag = {} self.location_pathloss = {} self.beacon = [] self.last_tag_location = None self.delta = value_json['Delta'].copy() for gateway in value_json['Gateway']: for datas in gateway['value']: data = gateway['value'][datas].copy() self.gateway[data['Mac']] = data['last'] self.gateway_sum[data['Mac']] = data['sum'] self.gateway_count[data['Mac']] = data['count'] self.last_gateway_sum[data['Mac']] = data['sum'][4] self.last_gateway_count[data['Mac']] = data['count'][4] self.gateway_kal[data['Mac']] = data['kalman'] self.last_gateway_kal[data['Mac']] = data['kalman'][4] if data['count'][4] > 2000: self.check_enough = 1 for datas in value_json['Tag']['value']: data = value_json['Tag']['value'][datas].copy() self.tag_kal[data['Mac']] = data['Last_kal'] self.dis_tag[data['Mac']] = 0 if not (value_json['Tag']['location'] is None): self.last_tag_location = value_json['Tag']['location'].copy() self.check_none = 0 for pathloss in value_json['Pathloss']: self.location_pathloss = pathloss['location'].copy() for datas in pathloss['value']: data = pathloss['value'][datas].copy() self.adjust[data['Mac']] = 0 self.pathloss_kal[data['Mac']] = data['Last_kal'] self.location[data['Mac']] = data['location'] self.dis_pathloss[data['Mac']] = self.calculate_path_dis( data['location'], pathloss['location']) #init estimate P = value_json['kalman']['P'] K = value_json['kalman']['K'] Q = value_json['kalman']['Q'] R = value_json['kalman']['R'] self.est = estimate_dis(P, K, Q, R) self.rssi1m = value_json['kalman']['RSSI1m']