Internet of Things (IoT) and Smart City in Pakistan

IoT in simple words is a technology which allows daily use objects to be sense, monitor and control from your smartphone. It includes everything from your hand watch to monitor your blood pressure, fuel alert in car, alert if your refrigerator out of eggs, coffee maker, air conditioner, smart doors and so on. All the devices embedded with sensors which allow devices to be smart enough and able to share information to its owner or communicate with other device. For example, your watch will tell your coffee machine to make your favorite coffee at morning wake up. Isn’t cool?

Main purpose of cultivating IoT is only to make life easier. IoT is revolutionizing many sectors such as agriculture, healthcare, transportation, smart homes, industries and manufacturing. Though, other countries are achieving target of smart city. In Singapore, the city can even detect if people are smoking in unauthorized zones or if people are throwing litter out of their buildings.

Pakistan is now in the state of adopting IoT in every sector. Pakistan telecom market is highly favorable with over 50 million number of 3G/4G subscribers. IoT is cost effective solution, as prices of sensors and processing devices are being decreased, while internet users are increasing.

Pakistan government needs to take some serious steps now for future. Although, Punjab government is leading in Information Communication Technology (ICT) and implementing free wifi project which aiming for smart city. But this is not enough, Pakistan needs stat-of-the-art research center for future smart city in each province to promote IoT and its application for smart cities, especially for the city like Karachi. Without this step, smart city is just a dream!

Engr. Yasir Iqbal

Karachi.

home automation using Internet of Things (IoT) by YnStek

Samsung unveils 8K Artificial Intelligence (AI) QLED TV

Samsung unveils its 8K smart Artificial Intelligence (AI) QLED TV at first look 2018 event. This LED with Ambient Mode turns your LED to intelligent mode. It has lots of features such as it can show you weather conditions and smart enough that can change picture according to sunny, rainy or snowy day. This LED TV connects your home to outside world. Using ambient mode, this LED can adjust its picture according to environment just like your background wall. Samsung introduced "one invisible connection" cable that supplies both power and data to LED. It's SmartThing app platform will let you control everything in your home.

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Wireless Controlling Home Appliances Using RF Trx 433Mhz 

DTMF Based Project

Dual-tone multi-frequency signaling DTMF Based Project using M8870 IC

By Yasir Iqbal

DESCRIPTION

In this project, which based on DTMF decoder Ic M8870, we showing the output of M8870 ic in 7 segment. The 4 bit data output of M8870 ic further connected with LS7447 decoder which is BCD decoder to 7 segment display unit.

Input tone from mobile gives to M8870 ic which further connected to BCD decoder LS7447 ic and then 7 segment.

WORKING

When we press any key from mobile (mobile keypad tone should be on) the tone goes to decoder ic which receiver certain key frequency and then converts to 4 bit data which further given to BCD decoder and then 7 segment connected to BCD decoder show that number which key pressed on mobile.

It can remotely operate when someone calls to that mobile (which is connected to circuit) and remotely press any dial number which can be received and circuit can show dial pressed number of caller .

Circuit Diagram

Components required

1. DTMF decoder IC (M-8870)                          5. BCD decoder 7447
2. Resistors (100kΩ; 70kΩ; 390kΩ;470Ω)         6. 7 Segment
3. Capacitors (0.1µFx 2)
4. Crystal oscillator (3.579545MHz)

Table showing DTMF Low and High frequency tones and decoded output

Uses of other pins:

• The entire process from frequency detection to latching of the data, is controlled by steering control circuit consisting of St/GT, Est pins, resistor (390kΩ) and a capacitor (0.1µF).

• 5th Pin, INH is an active high pin, inhibits detection of A, B, C, D tones of character.

• 6th Pin, PWDN is an (active high), inhibits the working of oscillator thus stops the working of our circuit.

• The 10th pin 10; TOE is the output enable pin which is active high logic and enables the latching of the data on the data pins Q0, Q1, Q2, and Q3.

• 15th Pin StD is the Data valid pin, turn out to be high on detection of valid DTMF tone or else it remains low.

• Pins 7 (OS1) and 8 (OS2) are used to connect crystal oscillator. An oscillator of frequency 3.579545 MHz is used here.

An Experimental Realization of Spectrum Sensing in Cognitive Radio.

An Experimental Realization of Spectrum Sensing in Cognitive Radio. 

The purpose of this project is to effectively utilize the bandwidth. The implementation of Cognitive radio makes sure full use of spectrum for secondary user while primary user (licensed user) is not available. Spectrum sensing is the function of cognitive radio which responsible to sense and understand its spectrum environment then detect unused spectrum in licensed band. The research paper on this project has been published in 2nd International Electrical Engineering Conference IEEC 2017 here.

Proposed Work

We have implemented an essential part of cognitive radio which is termed as spectrum sensing. As described above the spectrum sensing is a technique by which we determine which part of the licensed user spectrum is available. This spectrum sensing technique has many algorithms such as ED, MFD and FD. We have implemented ED (energy detection).

For this purpose the platform used are MATLAB and raspberry pi. The MATLAB is used as a PU or licensed user and raspberry pi act as SU or unlicensed user.

In this scenario the PU has five channels. On these five channels, MATLAB randomly allocate the user and starts transmission. This can be shown in the figure below.

Fig ure 6.1: PU Transmission

It is clear from the above figure that out of 5 channels the 1^st, 4^th  and 5^th channels are allocated to PU. Now the MATLAB transmits the signal to raspberry pi. The raspberry pi and MATLAB are connected via Ethernet cable.

Raspberry pi which is our sensor after receiving the signal performs FFT. After performing FFT the energy is calculated. The calculated energy is then compared with the predefined threshold. The threshold can be static and it could be variable depending upon the selection.

If the value of energy of the channel is less than the threshold then PU is not present else it is present. The channels which are not used by the PU are called spectrum holes. As shown in the figure 6.1.

Figure 6.2: Indicating Spectrum holes And PU

The SU (Raspberry pi) starts transmission on the Spectrum holes. This can be shown in figure 6.2.

Figure 6.3: SU Transmission on Spectrum Holes

Process

·         Generate Channels Randomly: We generated five channels on different frequencies and set a center frequency for each channel. As we are not working on real spectrum, we have generated channels of our own through MATLAB.

·         Sensing: Spectrum is sensed by Raspberry Pi and PSD/ energy of each channel is calculated in this step by calculating the energy and summing it up.

·         Threshold: we have set a fixed threshold, on calculating energy of channels it has been comparing to a threshold.

·         Decision: If the calculated energy is less than the threshold it detects that PU is absent and if the calculated energy is greater than threshold it detects that the PU is present.

·         Allocation: On detecting which of the channels are vacant, Raspberry Pi allocates those channels to a secondary user which can use the channel until PU resumes its transmission.

Results And Simulation

The results we have after using algorithm of energy detection and coding on Raspberry Pi are shown as follows.

We run the algorithm of energy detection on Raspberry pi and show the results through graphs and on circuit through LEDs.

      

Figure 6.4: MATLAB results (a)

The above graph shows the detection of primary user. On x-axis frequencies are mentioned and on y-axis mentioned power. In above graph, channel 1st, 3rd and channel 5th indicate the presence of signal whereas the other three channels are vacant indicating the spectrum holes.

                                                              Figure 6.5: MATLAB results (b)

This graph shows that the spectrum holes are now in use by secondary user. In figure. we received no primary user on channel-2 and channel-4, after sensing one out of these two channels are allocated to secondary user for transmission.

Presentation In Model Form.