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Nuclear and Chemical data with Plug-Unplug Systematics [MQ2 MQ3 MQ4 MQ5 MQ6 MQ7 MQ8 MQ9 MQ131 MQ135 MQ136 MQ137 MQ303A MQ309A Geiger Counter] Multi-Purpose that can configure with SQL and PHP, save data, do data science with Python, color scale with Lidar, deep learning with yolov9, objects with Pixy2 and location with GPS system Discovery Vehicle.

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Adjustable with Plug-Unplug Systematics Multi-Purpose Modular Discovery Vehicle with Nuclear and Chemical Data Calculation System

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SpaceRover

Discovery Vehicle

Nuclear and Chemical Data Calculation System with Plug-Unplug Systematics

Adjustable Data System

MQ-135

MQ-135

MQ-2

MQ-2

MQ-3

MQ-3

MQ-4

MQ-4

MQ-5

MQ-5

MQ-6

MQ-6

MQ-7

MQ-7

MQ-8

MQ-8

MQ-9

MQ-9

MQ131

MQ131

MQ-136

MQ-136

MQ-137

MQ-137

MQ303A

MQ303A

MQ309A

MQ309A

Google Maps with Data Calculation System

GoogleMaps

3D Lidar Scale with 3D lidar Data Mapping System

tab 3d-lidar-scale lidar1 lidar2 lidar3 lidar4

Saving Values to the Database with Plug-Unplug Feature

sqlfordata

SQL for MQ-135

sqlmq135

SQL for 3D lidar Data Mapping System

sqllidar

Real-time Object Tracking With AI Based Pixy2

Data Science and Regression

Formulla

  1. ppm = a*ratio^b (a: valuea b: valueb)
  2. ppm = 10^[(log10(ratio)-b)/m] (m: logm b: logb)

If R^2 equals 1 :

a*ratio^b = 10^[(log10(ratio)-b)/m]
logm = valueb, logb = log10(valuea)

1]

loghello

[(1,10), (2,4), (3,3)]

loge(b) = ln(b)

(ln(1),ln(10)) for ≈ (0,2.3026)

(ln(2),ln(4)) ≈ (0.6931,1.3863) and

(ln(3),ln(3)) ≈ (1.0986,1.0986)

b = ∑ i=1 n (x i − x ˉ ) 2 ∑ i=1 n (xi − xˉ)(yi−yˉ)

ln(x):(0,0.6931,1.0986)ln(y):(2.3026,1.3863,1.0986)ln(y)ˉ=(2.3026+1.3863+1.0986)/3≈1.5958

ln(x)ˉ=(0+0.6931+1.0986)/3≈0.5972

b = (0−0.5972)(2.3026−1.5958)+(0.6931−0.5972)(1.3863−1.5958)+(1.0986−0.5972)(1.0986−1.5958)/(0−0.5972)^2+(0.6931−0.5972)^2+(1.0986−0.5972)^2 ≈ -1.2

ln(a) = − ln ˉ (y) - b ln ˉ (x) ≈ 1.5958−(−1.2)⋅0.5972≈2.31244

a=e^2.31244 ≈ 9.947

loghello

b ≈ -1.2

a ≈ 9.947

2]

y = mx+ n
n = b
log10(y) = m*log10(x) + b

-b = m*log10(x) - log10(y)

last b = log10(y) - m*log10(x)

m = (y - y0) / (x - x0)

m = (log10(y) - log10(y0)) / (log10(x) - log10(x0))

if y= a*x^b:

last m = log10(y/y0) / log10(x/x0)

m = slope of the line

b = intersection point

m = log10(y/y0) / log10(x/x0)

b = log10(y) - m*log10(x)

    if r_squared >= 0.9995:
        print("R-squared value for {gas name} is above 0.9995, plotting against first and last values.")
        
        x0, y0 = x[0], y[0]
        xn, yn = x[-1], y[-1]
        b = np.log10(yn/y0) / np.log10(xn/x0)
        a = 10**(np.log10(yn) - b * np.log10(xn))
        b2 = np.log10(yn) - b * np.log10(xn)
        b2_rounded = round(b2, 4)
        a_rounded = round(a, 4)
        b_rounded = round(b, 4)

The first formula is determined according to all points, while the second formula is determined according to the first and last point. Therefore, in order to collect them all in the same formula and to increase the accuracy rate, we used the method in the second formula and took the logarithm (if R^2 = 1 (%100) always: logm = valueb, logb = log10(valuea)) for slopes greater than 99.95% and collected them all in the first formula, thus increasing the accuracy rate without having to use 2 different formulas.

MQDataScience

MQ3datascience

MQ-2

NewCurve:

MQ2curve

OldCurve:

MQ2curve

MQ-3

NewCurve:

MQ3curve

OldCurve:

MQ3curve

MQ-4

NewCurve:

MQ4curve

OldCurve:

MQ4curve

MQ-5

NewCurve:

MQ5curve

OldCurve:

![MQ5curve](https://github.com/abcdaaaaaaaaa/MQSpaceData.h/assets/108553778/5cb6f4f4-2d24-4e10-be19-849f186f0332

MQ-6

NewCurve:

MQ6curve

OldCurve:

MQ6curve

MQ-7

NewCurve:

MQ7curve

OldCurve:

MQ7curve

MQ-8

NewCurve:

MQ8curve

OldCurve:

MQ8curve

MQ-9

NewCurve:

MQ9curve

OldCurve:

MQ9curve

MQ131

NewCurve:

MQ131curve

OldCurve:

MQ131curve

MQ-135

NewCurve:

MQ135curve

OldCurve:

MQ135curve

MQ-136

NewCurve:

MQ136curve

OldCurve:

MQ136curve

MQ-137

NewCurve:

MQ137curve

OldCurve:

MQ137curve

MQ303A

NewCurve:

MQ303Acurve

OldCurve:

MQ303Acurve

MQ309A HIGH SENSIVITY FOR CH4

NewCurve:

MQ309Acurve

OldCurve:

MQ309Acurve

MQ-309A LOW SENSIVITY FOR CO

NewCurve:

MQ309A-LOW-curve

OldCurve:

MQ309A-LOW-curve

DataScience

MQ3datascience

MQ-2:

MQ2Science

MQ-3:

MQ3Science

MQ-4:

MQ4Science

MQ-5:

MQ5Science

MQ-6:

MQ6Science

MQ-7:

MQ7Science

MQ-8:

MQ8Science

MQ-9

MQ9Science

MQ131:

MQ131Science

MQ-135:

MQ135Science

MQ-136:

MQ136Science

MQ-137:

MQ137Science

MQ303A:

MQ303AScience

MQ309A

MQ309AScience

Deep-Learning with yolov9

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Nuclear and Chemical data with Plug-Unplug Systematics [MQ2 MQ3 MQ4 MQ5 MQ6 MQ7 MQ8 MQ9 MQ131 MQ135 MQ136 MQ137 MQ303A MQ309A Geiger Counter] Multi-Purpose that can configure with SQL and PHP, save data, do data science with Python, color scale with Lidar, deep learning with yolov9, objects with Pixy2 and location with GPS system Discovery Vehicle.

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