As the matter of fact, our experienced technical professionals are well qualified and ready to provide appropriate guidance. Without any delay, let’s see the list of titles for the WSN research projects using python in the following.
- Online indoor localization using DOA of wireless signals
- Statistical method based fault detection algorithm for wireless sensor networks
- Localization system in wireless sensor networks
- Vehicle to vehicle communication system using IoT
Next, we have highlighted the sample source code based on python for the trajectory process among the nodes.
import numpy as np
import matplotlib.pyplot as plt
def assemble(X2,Y2):
pos=np.zeros([len(X2),2])
for i in range(len(X2)):
pos[i]=np.matrix([[X2[i],Y2[i]]])
return pos
X1 = np.arange(50,150,1)
Y1 = np.arange(50,150,1)
tra1=assemble(X1,Y1)
X2=np.arange(0,200,1)
Y2=-np.exp(0.0266*X2) +200
tra2 = assemble(X2,Y2)
x1 = np.arange(0,220,1)
y1 = np.arange(200,180,-.09)
x2 = np.arange(220,-10,-1)
y2 = np.arange(179,129,-.2173)
dy = .5
x3 = np.arange(-10,200,1)
y3 = np.arange(128,0,-.609)
x1= np.append(x1,x2)
x = np.append(x1,x3)
y1 = np.append(y1,y2)
y = np.append(y1,y3)
path = np.zeros((len(x),2))
for i in range(len(x)):
path[i] = np.matrix([x[i],y[i]])
def smooth(path,data_weight=0.3
,smooth_weight=0.15, tolerance = 0.01):
newpath = path
change = tolerance
c =0
while c < 1000 :
change =0.
for i in range(1,len(path)-1):
if not(i ==99 or i==100 or i==199 or i==200 or i==299):
for j in
range(len(path[0])):
aux =
newpath[i][j]
newpath[i][j] += data_weight * (path[i][j]-newpath[i][j])
newpath[i][j] += smooth_weight * ( newpath[i-1][j] + newpath[i+1][j] - 2.*newpath[i][j]
)
change += abs(aux - newpath[i][j])
else :
for j in
range(len(path[0])):
aux = newpath[i][j]
newpath[i][j] += 0.8 * (path[i][j]-newpath[i][j])
newpath[i][j] += 0.1 * ( newpath[i-1][j] + newpath[i+1][j] - 2.*newpath[i][j] )
change += abs(aux - newpath[i][j])
change += 0.005
c+=1
return newpath
tra3 = smooth(path)
#np.save('tra1.npy',tra1)
plt.plot(tra1[:,0],tra1[:,1])
plt.show()
plt.plot(tra2[:,0],tra2[:,1])
plt.show()
plt.plot(tra3[:,0],tra3[:,1])
plt.show()
Then, we have to implement the wireless sensor network in python through going to the menu and click the run module option.
At last, we have highlighted the result which is obtained through execution of wireless sensor network in python.
Don’t worry if you guys have any doubts, because our technical experts are always ready to help you out.