Companies that produce energy transmit it to any or all households via a power grid, which is a regulated power transmission hub that acts as a middleman. When a power grid fails, the whole area it serves is blacked out. To ensure smooth and effective functioning, a power grid monitoring system is required. Computer vision is among the most commonly utilized and active research applications in the world of video surveillance. Though a lot has been accomplished in the field of power grid surveillance, a more effective compression method is still required for large quantities of grid surveillance video data to be archived compactly and sent efficiently. Video compression has become increasingly essential with the advent of contemporary video processing algorithms. An algorithm’s efficacy in a power grid monitoring system depends on the rate at which video data is sent. A novel compression technique for video inputs from power grid monitoring equipment is described in this study. Due to a lack of redundancy in visual input, traditional techniques are unable to fulfill the current demand standards for modern technology. As a result, the volume of data that needs to be saved and handled in live time grows. Encoding frames and decreasing duplication in surveillance video using texture information similarity, the proposed technique overcomes the aforementioned problems by Robust Particle Swarm Optimization (RPSO) based run-length coding approach. Our solution surpasses other current and relevant existing algorithms based on experimental findings and assessments of different surveillance video sequences utilizing varied parameters. A massive collection of surveillance films was compressed at a 50% higher rate using the suggested approach than with existing methods.

Conventional magnetically coupled resonant wireless power transfer systems are faced with resonant frequency splitting phenomena and impedance mismatch when a receiving coil is placed at misaligned position. These problems can be avoided by using uniform magnetic field distribution at receiving plane. In this paper, a novel 3D transmitting coil structure with improved uniform magnetic field distribution is proposed based on a developed optimization method. The goal is to maximize the average magnetic field strength and uniform magnetic field section of the receiving plane. Hence, figures of merit (FoM1 and FoM2) are introduced and defined as product of average magnetic field strength and length or surface along which uniform magnetic field is generated, respectively. The validity of the optimization method is verified through laboratory measurements performed on the fabricated coils driven by signal generator at operating frequency of 150 kHz. Depending on the allowed ripple value and predefined coil proportions, the proposed transmitting coil structure gives the uniform magnetic field distribution across 50% to 90% of the receiving plane.

Wireless power transfer has been proved promising in various applications. The homogeneous winding method in loosely coupled transformers incurs unnecessary intense magnetic field distribution in the center and causes extra magnetic loss. An inhomogeneous winding method is proposed in this paper, and a relatively homogeneous magnetic field distribution inside the core is achieved. This paper investigated the magnetic loss of homogeneous winding and inhomogeneous winding for wireless power transfer. A theoretical model was built to evaluate magnetic loss under inhomogeneous winding. The coupling coefficient and magnetic loss were investigated individually and comparisons were made between different width ratio combinations. Theoretical analysis was validated in experiments.

The widespread deployment of the Internet of Things (IoT) requires the development of new embedded systems, which will provide a diverse array of different intelligent functionalities. However, these devices must also meet environmental, maintenance, and longevity constraints, while maintaining extremely low-power consumption. In this work, a batteryless, low-power consumption, compact embedded system for IoT applications is presented. This system is capable of using a combination of hybrid solar and radiofrequency power sources and operates in the 900 MHz ISM band. It is capable of receiving OOK or ASK modulated data and measuring environmental data and can transmit information back to the requester using GFSK modulated data. The total consumption of the system during its sleep state is 920 nW. Minimum power required to operate is −15.1 dBm or 70 lux, when using only radiofrequency or solar powering, respectively. The system is fully designed with components off the shelf (COTS).

In this paper, a multiantenna wireless transmitter communicates with an information receiver while radiating RF energy to surrounding energy harvesters. The channel between the transceivers is known to the transmitter, but the channels between the transmitter and the energy harvesters are unknown to the transmitter. By designing its transmit covariance matrix, the transmitter fully charges the energy buffers of all energy harvesters in the shortest amount of time while maintaining the target information rate toward the receiver. At the beginning of each time slot, the transmitter determines the particular beam pattern to transmit with. Throughout the whole charging process, the transmitter does not estimate the energy harvesting channel vectors. Due to the high complexity of the system, we propose a novel deep Q-network algorithm to determine the optimal transmission strategy for complex systems. Simulation results show that deep Q-network is superior to the existing algorithms in terms of the time consumption to fulfill the wireless charging process.

An approach to improve wireless power transfer (WPT) to implantable medical devices using loop antennas is presented. The antenna exhibits strong magnetic field and dense flux line distribution along two orthogonal axes by insetting the port inside the antenna area. This design shows excellent performance against misalignment in the y-direction and higher WPT as compared with a traditional square loop antenna. Two antennas were optimized based on this approach, one wearable and the other implantable. Both antennas work at both the ISM (Industrial, Scientific, and Medical) band of 433 MHz for WPT and the MedRadio (Medical Device Radiocommunications Service) band of 401–406 MHz for communications. To test the WPT for implantable medical devices, a miniaturized rectifier with a size of 10 mm × 5 mm was designed to integrate with the antenna to form an implantable rectenna. The power delivered to a load of 4.7 kΩ can be up to 1150 μW when 230 mW power is transmitted which is still under the safety limit. This design can be used to directly power a pacemaker, a nerve stimulation device, or a glucose measurement system which requires 70 μW, 100 μW, and 48 μW DC power, respectively.

Wireless energy harvesting is an effective way to power condition monitoring sensors which are the basis of smart grid. In this paper, a new free-standing I-shaped core is designed to scavenge electromagnetic energy from large alternating current. An I-shaped core can guide more magnetic flux by adding a pair of magnetic flux collector plates at both ends of the rod core. It weakens the core demagnetization field and enables more energy to be collected. Since a magnetic field line can be bent with high-permeability soft magnetic materials, a highly efficient grid-shaped coil is proposed. Compared with the I-shaped coil, its weight is lighter and power density is higher. A Mn-Zn ferrite with high relative permeability and ultralow conductivity can effectively reduce eddy current loss, which proves to be the most suitable material. The measured open circuit voltage agrees well with the theoretical value. The experimental results show that the output power can reach 4.5 mW when the I-shaped coil is placed in a magnetic flux density of 6.5 μTrms. The power density is 7.28 μW/cm3. Therefore, the proposed design can be very effective for supplying condition monitoring sensors.