Evidential representation of using the modern devices and decisionmaking feasibility in Pakistan

In the long run of modernity and technicality, the use of smart appliances in every field of life has been the need and demand of the era. The evidential representation by using modern devices is permissible in various developed judiciary cultures of the world. Pakistani courts and the judiciary system are also adopting modern devices to present the evidence in the courts for authentic decision-making. The articles and sections of Qanun-e-Shahadat order, 1984 and Electronic Certification Accreditation Council under Section 18 clarified using modern technologies to present the evidence in the courts with state and religion's perspectives of acceptability. The study descriptively demonstrated various types of modern devices use for evidential representation of offenders data; press reports and press clips, fax, email and internet evidence, cell phones, computer-related data, audio recordings, photographs and screenshots, video films and video cassettes, CCTV footage, polygraphy test and DNA test. In each type of modern evidential representation, the registered, recorded and solved cases have also been mentioned as proof of modern devices application in court decision-making feasibility. The study found that the unapproached low-class sector of society feels reluctant to rely on and use modern devices for court hearings and decision-making due to unawareness and unavailability of modern resources. There is also the issue of some insecurities and inadequacies of using modern devices as evidential representation because of editing, cropping and regenerating the duplicate evidence that could not be verified due to lack of technical flaws and advancement of computerized technology.

Towards Optimal Management in Microgrids: An Overview

A microgrid is a set of decentralized loads and electricity sources, mainly renewable. It can operate connected to and synchronized with a traditional wide-area synchronous grid, i.e., a macrogrid, but can also be disconnected to operate in “island mode” or “isolated mode”. When this microgrid is able to manage its own resources and loads through the use of smart meters, smart appliances, control systems, and the like, it is referred to as a smart grid. Therefore, the management and the distribution of the energy inside the microgrid is an important issue, especially when operating in isolated mode. This work presents an overview of the different solutions that have been tested during the last few years to manage microgrids. The review shows the variety of mature and tested solutions for managing microgrids with different configurations and under several approaches.

IoT for smart home system

<p>This paper examines the integration of smart home and solar panel system that is controlled and monitored using IoT (internet ofthings). To enable the smart home system to monitor the activity within the house and act according to the current conditions, it is equipped with several sensors, actuators and smart appliances. All of these devices have to be connected to a communication network, so they can communicate and provide services forthe smart home’s in habitants. The smart home system was first introduced to provide comfort and convenience, but later it should also address many other things, e.g. the importance of the efficient use of energy or electricity and hybrid use of energy sources. A solar panel is added to the smart home prototype and its addition is studied. Adaptive linear neural network is implemented in the prototype as an algorithm for predicting decisions based on the current conditions. The construction of the proposed integrated systemis carried out through several procedures, i.e. the implementation of the adaptive linear neural network (ADALINE) as the neural network method, the design of the prototype and the testing process. This prototype integrates functionalities of several household appliances into one application controlled by an Android-based framework.</p>

Learning natural language interfaces with neural models

Language is the primary and most natural means of communication for humans. The learning curve of interacting with various services (e.g., digital assistants, and smart appliances) would be greatly reduced if we could talk to machines using human language. However, in most cases computers can only interpret and execute formal languages.

Appliance scheduling optimization with micro-grid in smart home network

The fast emerging smart grid technology provides greater information flow, flexibility and control to both electricity consumers and electricity suppliers. Of these benefits, the two way flow of information between consumer and electricity producer in smart grid opened new vistas of applications. Smart home appliances are connected to home area network (HAN) to co-ordinate power usage demanded for the home under control. We are, therefore, witnessing an increasing interest in smart homes from the point of view of optimal energy management, renewable green energy sources and smart appliances. Hence, the problem of scheduling of smart appliances operations in a given time range with set of energy sources like national grid and local generation micro-grid is investigated in this thesis. Renewable energy source that is adopted in this thesis is a photovoltaic panel as a power producing appliance. Appliance operation is modeled in terms of un-interruptible sequence phases, given in load demand profile with a goal of minimizing electricity cost fulfilling duration, energy requirement, and user preference constraints. An optimization algorithm which can provide a schedule plan for smart home appliances usage is proposed based on the mixed integer linear programming technique. The effect of adding a photovoltaic system in the home results in reduction of electricity bill and the peak demand of the home and export of energy to the national grid in times when solar energy production is more than the demand of the home. The situation is modeled using Matlab with Yalmip library to exploit the state-of-the-art Gurobi solver for obtaining the timing of appliance scheduling in the smart home in comparable time to be true as real time process for demand side management.

Appliance scheduling optimization with micro-grid in smart home network

The fast emerging smart grid technology provides greater information flow, flexibility and control to both electricity consumers and electricity suppliers. Of these benefits, the two way flow of information between consumer and electricity producer in smart grid opened new vistas of applications. Smart home appliances are connected to home area network (HAN) to co-ordinate power usage demanded for the home under control. We are, therefore, witnessing an increasing interest in smart homes from the point of view of optimal energy management, renewable green energy sources and smart appliances. Hence, the problem of scheduling of smart appliances operations in a given time range with set of energy sources like national grid and local generation micro-grid is investigated in this thesis. Renewable energy source that is adopted in this thesis is a photovoltaic panel as a power producing appliance. Appliance operation is modeled in terms of un-interruptible sequence phases, given in load demand profile with a goal of minimizing electricity cost fulfilling duration, energy requirement, and user preference constraints. An optimization algorithm which can provide a schedule plan for smart home appliances usage is proposed based on the mixed integer linear programming technique. The effect of adding a photovoltaic system in the home results in reduction of electricity bill and the peak demand of the home and export of energy to the national grid in times when solar energy production is more than the demand of the home. The situation is modeled using Matlab with Yalmip library to exploit the state-of-the-art Gurobi solver for obtaining the timing of appliance scheduling in the smart home in comparable time to be true as real time process for demand side management.