A Smart Heating System for Energy Management using an Enhanced Kinetic User I...Editor IJAIEM
Mohamed Amine Rafkaoui 1, Nabil Birouk1, Ghita Lahlou1, Yassine Salih Alj1
1 School of Science and Engineering Al Akhawayn University in Ifrane Ifrane, Morocco
ABSTRACT
Improving energy efficiency of buildings is becoming increasingly critical to reduce energy consumption and to solve the
environmental crisis while ensuring thermal comfort. Heaters are among the appliances that consume a significant amount of
energy. This paper introduces a way to optimize the energy consumption of heating systems by adjusting the room temperature
and minimizing the heating periods while keeping the comfort of the occupants. The kinetic user interface combines motion
awareness and activity recognition to regulate the temperature depending on the type of activity the user is carrying out.
However, changing the temperature is a slow process. Starting to adjust the temperature exactly when the user starts an activity
might be too late and might cause physical discomfort. Consequently, we propose an enhanced kinetic user interface that takes
into account not only the user’s current activity but also the time the room needs to heat up or cool down.
Keywords: Smart heater, Temperature adjustment, Energy consumption, Kinetic User Interface
Application for Logical Expression Processing csandit
Processing of logical expressions – especially a conversion from conjunctive normal form (CNF) to disjunctive normal form (DNF) – is very common problem in many aspects of information retrieval and processing. There are some existing solutions for the logical symbolic calculations, but none of them offers a functionality of CNF to DNF conversion. A new application for this purpose is presented in this paper.
Object-Oriented Software Engineering (commonly known by acronym OOSE) is an object-modeling language and methodology.It has a quite details about the object oriented software engineering in Software engineering courses
A PROPOSED FUZZY LOGIC APPROACH FOR CONSERVING THE ENERGY OF DATA TRANSMISSIO...IJCNCJournal
One of the primary challenges facing the Internet of Things is the reservation and efficient consumption of
energy resources, especially in those types of applications that require continuous monitoring or suffer
from lacking ongoing energy resources. Despite this, the indoor temperature and humidity monitoring
systems are unconcerned about the insignificant amount of energy consumed during critical times when
sending unimportant or useless data to the control room’s servers. This paper proposes a fuzzy logic-based
approach for reducing the amount of energy spent in indoor temperature and humidity monitoring systems
by filtering data that is sent to servers based on several surrounding circumstances such as time of data
recording and current energy consumption amount while maintaining constant monitoring. The
experimental results on the Appliances Energy Prediction dataset show that the proposed fuzzy-based
approach successfully reduces energy consumption in temperature and humidity monitoring systems by
11.8%.
A Smart Heating System for Energy Management using an Enhanced Kinetic User I...Editor IJAIEM
Mohamed Amine Rafkaoui 1, Nabil Birouk1, Ghita Lahlou1, Yassine Salih Alj1
1 School of Science and Engineering Al Akhawayn University in Ifrane Ifrane, Morocco
ABSTRACT
Improving energy efficiency of buildings is becoming increasingly critical to reduce energy consumption and to solve the
environmental crisis while ensuring thermal comfort. Heaters are among the appliances that consume a significant amount of
energy. This paper introduces a way to optimize the energy consumption of heating systems by adjusting the room temperature
and minimizing the heating periods while keeping the comfort of the occupants. The kinetic user interface combines motion
awareness and activity recognition to regulate the temperature depending on the type of activity the user is carrying out.
However, changing the temperature is a slow process. Starting to adjust the temperature exactly when the user starts an activity
might be too late and might cause physical discomfort. Consequently, we propose an enhanced kinetic user interface that takes
into account not only the user’s current activity but also the time the room needs to heat up or cool down.
Keywords: Smart heater, Temperature adjustment, Energy consumption, Kinetic User Interface
Application for Logical Expression Processing csandit
Processing of logical expressions – especially a conversion from conjunctive normal form (CNF) to disjunctive normal form (DNF) – is very common problem in many aspects of information retrieval and processing. There are some existing solutions for the logical symbolic calculations, but none of them offers a functionality of CNF to DNF conversion. A new application for this purpose is presented in this paper.
Object-Oriented Software Engineering (commonly known by acronym OOSE) is an object-modeling language and methodology.It has a quite details about the object oriented software engineering in Software engineering courses
A PROPOSED FUZZY LOGIC APPROACH FOR CONSERVING THE ENERGY OF DATA TRANSMISSIO...IJCNCJournal
One of the primary challenges facing the Internet of Things is the reservation and efficient consumption of
energy resources, especially in those types of applications that require continuous monitoring or suffer
from lacking ongoing energy resources. Despite this, the indoor temperature and humidity monitoring
systems are unconcerned about the insignificant amount of energy consumed during critical times when
sending unimportant or useless data to the control room’s servers. This paper proposes a fuzzy logic-based
approach for reducing the amount of energy spent in indoor temperature and humidity monitoring systems
by filtering data that is sent to servers based on several surrounding circumstances such as time of data
recording and current energy consumption amount while maintaining constant monitoring. The
experimental results on the Appliances Energy Prediction dataset show that the proposed fuzzy-based
approach successfully reduces energy consumption in temperature and humidity monitoring systems by
11.8%.
A Proposed Fuzzy Logic Approach for Conserving the Energy of Data Transmissio...IJCNCJournal
One of the primary challenges facing the Internet of Things is the reservation and efficient consumption of energy resources, especially in those types of applications that require continuous monitoring or suffer from lacking ongoing energy resources. Despite this, the indoor temperature and humidity monitoring systems are unconcerned about the insignificant amount of energy consumed during critical times when sending unimportant or useless data to the control room’s servers. This paper proposes a fuzzy logic-based approach for reducing the amount of energy spent in indoor temperature and humidity monitoring systems by filtering data that is sent to servers based on several surrounding circumstances such as time of data recording and current energy consumption amount while maintaining constant monitoring. The experimental results on the Appliances Energy Prediction dataset show that the proposed fuzzy-based approach successfully reduces energy consumption in temperature and humidity monitoring systems by 11.8%.
3.
As mentioned earlier, strong cohesion implies that all
parts of a component should have a close logical
relationship with each other. That means, in case some
kind of change is required in the software, all the related
pieces are found at one place.
A class will be cohesive if most of the methods defined in
a class use most of the data members most of the time. If
we find different subsets of data within the same class
being manipulated by separate groups of functions then
the class is not cohesive and should be broken down as
shown in the above slide.
Example of Cohesion
5.
Consider a heat regulatory system for a room as
shown below.
Intelligence Distribution
6.
In this case, the room is not encapsulated as one
entity and three different objects namely Desired
Temp, Actual Temp, and Occupancy maintain
necessary information about a room. In this case the
Heat Flow Regulator has to communicate with three
different objects.
Intelligence Distribution
8.
If we encapsulate the three objects into one Room object
as shown in the above slide, then the Heat Flow Regulator
will need to communicate with one object, hence the
overall coupling of the system will be reduced.
This happened because in the first case intelligence is
distributed while in the second case it is encapsulated.
However, the control is still centralized as the Heat Flow
Regulator has the control logic that first analyses the
values from different queries and then makes a decision
about turning the furnace on of off. We can improve the
situation even further by delegating this responsibility to
the Room object as shown below.
Intelligence Encapsulation
10.
Intelligence Distribution
By doing that we reduce coupling even further
because now we have made Room more cohesive by
putting the function with the related data and have
thus reduced the number and types of messages
being sent from the regulator to the room.