1. Slide 2
Introduction#
The Internet of Things (IoT) represents a vision of a highly interconnected mesh of smart
devices exchanging data, without human intervention, about every aspect of each smart
device's environment. Powering these devices remains a significant challenge, but one well
suited to energy-harvesting solutions. Using available energy transducers and ICs, engineers
can create zero-power smart devices able to address the power challenges of an evolving
IoT. Creating devices with intelligent battery-less option is growing slowly. Mainly
commercial and military fields demand such kind of products. They usually rely on wireless
sensor nodes (WSN) with low power consumption.
Mostly all such devices would be provided with super capacitors to give it longer life span.
Even with such
features these devices are deployed to replacement of batteries when they are drained out.
So the need of self powered. devices comes into picture. These devices usually take energy
from ambient environment by
harvesting the required power for the device. Depending on need, such harvesting schemes
can be of
continuous mode or instantaneous mode
The IoT expands the reach of the Internet to individual embedded devices designed to
interact with machines, extending the familiar paradigm of a web of human users connected
through smartphones, tablets, and computers. Unlike those user systems, embedded
devices connected through the IoT must continue to operate with self-contained power and
without expectation that a human user will be available to monitor available power, change
a battery, or plug the device into a power outlet.
In many cases, IoT devices will be expected to operate for years beyond the ability of even
the most advanced battery technology to deliver sufficient operating power. At the same
time, many smart sensor applications for these embedded devices require relatively few
components (Figure 1) to transmit sensor data wirelessly to other smart devices and
upstream servers.
Slide 3
Picture fig 1: In concept, a typical wireless sensor node in the IoT is a simple device that
combines an MCU with subsystems for sensors and wireless connectivity. System power
remains a challenge for IoT devices expected to operate unattended for years

2. Regardless of the type of ambient energy, designers can face a significant challenge in
building energy-harvesting power supplies capable of extracting maximum power from
sources that can vary their energy output significantly from one moment to the next. Energy
transducers such as piezoelectric devices used to convert vibrational energy into a voltage
output, deliver maximum energy when operating at the resonant frequency of the
vibrational source, and when operating into a load designed to match piezoelectric output
impedance.
Slide 4
What is piezoelectricity?
There are multiple techniques for converting vibrational energy to electrical energy. The
most prevalent three are electrostatic, electromagnetic, and piezoelectric conversion . A

3. majority of current research has been done on piezoelectric conversion due to the low
complexity of its analysis and fabrication. Most research, however, has targeted a specific
device scale. Little research comparing power output across different scales has been done
for piezo harvesters, though scaling effects have been discussed briefly in some works.
Piezoelectricity is the electric charge that accumulates in certain solid materials in response
to applied mechanical stress.
Piezoelectric materials A majority of piezoelectric generators that have been fabricated and
tested use some variation of lead zirconate titanate (PZT). Typically, PZT is used for
piezoelectric energy harvesters because of its large piezoelectric coefficient and dielectric
constant, allowing it to produce more power
for a given input acceleration [10]. Another less common material is aluminum nitride (AlN).
Slide 5
Circuit design for energy harvesting
The circuit works as following. Charges generated by the piezoelectric generator are first
transferred to the capacitor C2, while the regulator and transmitter (as load RL) is isolated
by the MOSFET,Q2. The zener diode D5 connecting at the base of bipolar transistor Q1
breaks down when the voltage across the capacitor C1 exceeds a preset value. This turns Q1
on. Once Q1 is turned on, the voltage across R2, adjustable by the potential divider formed
by R1 and R2, exceeds the threshold voltage of MOSFET Q2 and it turns on Q2. Thus, the
source ground and the load ground is connected and C1 starts discharging to the load
(regulator and the RF transmitter). R3 acts as the latch to ensure that
Q1, and in turn Q2, remains on even the voltage across C1 drops below the zener diode’s
breakdown voltage. When the capacitor drops below 4.5 V, the low-battery line on the
regulator (not shown) is pulled down, transmitting a negative pulse through an external
capacitor and turning Q1 off, inturn
deactivating Q2 and halting the discharge of C1.
Slide 5
The energy supply system that can be used to convert the energy of ambient mechanical
vibrations to electricity is used to power the wireless sensor node. In order to increase the

4. generated power and convert more mechanical energy effectively, an energy supply system
must be employed. Figure1 presents a schematic of the proposed system. It contains a
piezoelectric element, an energy conditioning unit, an energy storage unit, and an energy
management unit. The piezoelectric element converts the external vibration mechanical
energy to alternating power and outputs electrical energy to the energy storage unit
through the energy conditioning unit. In the energy conditioning unit, the controller runs an
active piezoelectric energy harvesting technology which will be discussed in the next
chapter. It outputs an optimal control voltage applied to the full-bridge circuit and the DC-
DC circuit. The energy storage unit which is used to store the generated electrical energy is
commonly are chargeable battery or a supercapacitor. The energy management unit
contains two parts, a smart switch and a voltage regulator, and monitors the voltage of the
energy storage unit. When the voltage of the energy storage unit is in the setting range, the
energy management unit can output a constant voltage to power the wireless sensor node.
Slide 6
Wireless sensor networks have been of great interests over the last few decades. Wireless
sensor networks are the integration of sensor technology, embedded computing
technology, modern network and wireless communication technology, distributed
information processing technology, and so on.
They can be used to monitor, sense, and collect the information on the environment or
objects by microsensors and transmit these information to the users. Therefore, they have
gained numerous applications such as military defense, industry and agriculture, city
management, biological and medical treatment, and environmental monitoring. The energy
supply system can run an adaptive active piezoelectric harvesting technology to generate an
optimal control voltage and improve harvested energy in the broadband.
The purpose of this paper is placed on resolving the two challenges i.e. narrow bandwidth
and low efficiency, by using the designed ultra-low power energy supply circuit to harvest
maximal energy for wireless sensor network nodes.
Conclusion
We have presented two models that have been proposed and verified by research scientists
in recent times.
The first one, the wireless sensor node: Compared to the classic energy harvesting
technology, Figure7presents the experimental and theoretical power of the energy
conversion unit. Because of the circuit efficiency, the harvested power is no longer a
constant for different excitation frequencies. The maximum power harvested by the active

5. circuit is 9.8 mW at the resonance frequency 85 Hz. In the non-resonant frequencies, the
experimental power regulated by the active piezoelectric energy harvesting technology does
not quickly reduce. The output power is up to 4 times larger than the power by the classic
energy harvesting technology in nonresonance frequencies.
One practical application on self-powered wireless smart dust temperature sensor network
was designed and implemented and the prototype system has an energy efficiency of 73.8%
and is capable of transmitting data packets successfully without any external power supply.