WO2013061300A1

WO2013061300A1 - A distributed monitoring method for achieving energy efficiency in buildings and apparatus therefor

Info

Publication number: WO2013061300A1
Application number: PCT/IB2012/055923
Authority: WO
Inventors: Girolamo DI FRANCIA; Saverio DE VITO; Grazia FATTORUSO
Original assignee: ENEA - Agenzia nazionale per le nuove tecnologie, l'energia e lo sviluppo economico sostenibile
Priority date: 2011-10-28
Filing date: 2012-10-26
Publication date: 2013-05-02
Also published as: ITRM20110571A1

Abstract

A pervasive and continuous distributed monitoring method for achieving energy efficiency in buildings and more in general in articulated complexes of buildings envisages the use of multisensor devices that have wireless-communication capacity, capacity for organization in mesh topologies, and capacity of on¬ board intelligence. These devices, appropriately located/distributed in the nodes of a wireless sensor network in the premises to be controlled, enable information to be obtained on the current state of the various premises of the building and of the energy- consuming systems operating therein in order to rationalize and optimize energy consumption. The corresponding apparatus envisages multi-sensor nodes, organized in a multilevel wireless sensor-network architecture, which is able both to exchange with one another the data gathered and locally pre-processed and forward them to a localized co-ordinator and control system.

Description

A DISTRIBUTED MONITORING METHOD FOR ACHIEVING ENERGY

EFFICIENCY IN BUILDINGS AND APPARATUS THEREFOR

DESCRIPTION

Object of the invention

The present invention relates to a real-time distributed monitoring apparatus and method for achieving energy efficiency in buildings (whether residential, commercial, or company buildings) based upon wireless multisensor modules provided with on^¬ board intelligence, capable of obtaining real-time information on energy consumption, quality of the air, environmental variables, and occupation of the premises.

These wireless smart multisensor devices are organized in multilevel architectures of smart sensor networks to enable pervasive and continuous distributed monitoring for control of energy efficiency in residential and non-residential buildings and in computer centres.

Description of the problem

The European Community, as likewise the international community, have devoted considerable effort for orienting today' s economy towards energy sustainability . The preset short-term targets are to reduce the emissions of greenhouse gases, increase consumption of energy from renewable sources, and optimize energy consumption by achieving energy efficiency.

Statistical studies and investigations conducted on the energy requirements of the various sectors of economy (residential and tertiary, transport, and industry sectors) have highlighted the considerable energy impact of buildings on the global consumption of the residential and tertiary sector. In Europe, for example, it is estimated that buildings in general are responsible for approximately 40% of the total use of energy (70% of electricity) as compared to 32% of industry and 28% of transports and, according to the forecasts, their energy demand is bound to increase in the next few years. In particular, computer centres have a considerable energy requirement that is currently estimated at around 40 TWh/yr and is bound to double in the coming years unless specific measures for achieving energy efficiency are defined and adopted. Residential buildings, instead, are responsible for 22% of total energy consumption, and the majority of the energy is used to maintain a comfortable internal environment (12% for air conditioning and 31% for heating) .

It is to be noted that, prior to the advent of policies of energy sustainability in the residential and tertiary sector together with the sectors of transport and industry, the energy properties of buildings were not generally taken into account during their building, nor much less the inefficiency of existing buildings was measured during their use. Only recently the vision of buildings from the standpoint of mere user of energy is evolving towards that of complex system that integrates models of distributed energy (energy from traditional plants integrated with energy from renewable sources) , and processes and technologies for a rational use of energy based upon high levels of efficiency without reducing the levels of quality and safety of the services or the comfort for users.

It is estimated that the awareness on the part of the user (from the man in the street to owners of services and infrastructures, to governors, etc.) of the consumption of energy-consuming systems present in the premises with which he interacts can determine a more rational and efficient use of the energy, favouring good practices and virtuous behaviours aimed at energy saving. Moreover, a pervasive and continuous monitoring of the energy consumption in buildings (from computer centres to commercial centres, from offices to dwellings) can determine a significant energy saving estimated at between 10% and over 15%.

However, currently the technologies, together with the competence, necessary for increasing the potential of energy saving of buildings are still undergoing definition and/or experimentation, and where, for specific buildings (for example, computer centres) , some solutions have been developed and marketed, basically they implement approaches of the measure-and- management type, not envisaging pervasive and continuous measurements.

State of the art

In this regard, from a study made on the existing patent and technico-scientific literature, it emerges that the existing sensor devices for control of energy efficiency in buildings are fundamentally clamp-type energy-absorption meters or ones that can be integrated in electric sockets (even more than one for a single electric socket) , capable of detecting the consumption levels of the network of energy-consuming systems present in a dwelling or office (see, for example, the patents Nos. US2011055116, US20100256828) .

Said devices have wireless-communication capacity but not mesh-routing capacity; namely, they cannot be organized in wireless sensor networks. They can, instead, be connected to the cables that reach the main switchboard of a dwelling or of an office making it possible to detect and keep under control the energy consumption of the entire network of energy-consuming systems present. In addition, they do not have on-board intelligence and envisage data-sink systems configured for filing, processing, and displaying, even remotely, the information acquired (see the patents Nos. US20100256828, US2011055116, KR100963161) . The sphere of application includes energy-consuming systems (electrical household appliances, lighting, HVAC systems, PCs, etc.) basically of dwellings and offices.

Hence, it is indispensable to provide a technology, that can be readily installed and used, which enables measurement in a pervasive and continuous way and control of energy consumption in buildings in order to rationalize the use of energy and ensure the maximum comfort for the users .

Description of the invention and its innovative characteristics

Consequently, constituting a subject of the invention is an innovative system for distributed, pervasive, and continuous monitoring for achieving energy efficiency in buildings and more in general in articulated complexes of buildings, which is based upon multisensor devices that have wireless-communication capacity, capacity for organization in mesh topologies, and capacity for on-board intelligence. These devices, appropriately located/distributed in the nodes of a wireless sensor network in the premises to be controlled, enable information to be obtained on the current state of the various premises of the building and of the energy-consuming systems operating therein in order to rationalize and optimize energy consumption.

Advantageously, according to the operating contexts, both physical quantities (such as electrical consumption, temperature, luminosity, presence, etc.) and chemical quantities (chiefly, relative humidity and volatile organic compounds) are monitored.

A strategy for optimizing the use of energy in buildings has in fact to be definable not only on the basis of the profiles of consumption of the energy- consuming systems that operate in the various premises of the building, but also on the knowledge of the state of operation and safety thereof. For example, knowing in a pervasive way the quality of the air of the premises enables implementation of efficient control strategies of HVAC systems (such as activation or deactivation of ventilation and air-conditioning systems on the basis of the levels of concentration of volatile organic compounds present in the air) , with consequent energy saving. Likewise, the pervasive and continuous knowledge of environmental conditions (temperature and humidity) of a computer centre, together with monitoring of the electrical consumption, enables control of proper operation of the cooling systems of rooms housing the computers by detecting any possible discrepancies (for example, mixing between hot air leaving the machines and cool air entering the room) . Optimization of the flows of air in a computer centre enables significant energy saving, raising the values of the energy-efficiency indices (for example, the PUE - power-usage effectiveness - index, which is the ratio between the total power absorbed by a data centre and the power used by IT apparatuses alone) and at the same time containing the state of wear of the computers .

For these purposes, the monitoring system forming the subject of the present invention envisages a node architecture that enables use of:

(1) clamp-type energy-absorption meters or ones that can be integrated in electric sockets through which to acquire data on electrical consumption;

(2) electronic noses of small dimensions with on- board intelligence for estimating locally the concentration of pollutants in the air and constructing an olfactive image of the environment in which they are immersed;

(3) integrated modules constituted by energy- absorption meters and temperature and humidity sensors specific for computer centres;

(4) movement sensors for detecting the presence and position of persons in the premises.

It is to be noted that the system proposed can integrate also other types of sensor nodes. In any case, the sensors described above enable monitoring of the most significant physico-chemical quantities for an efficient use of energy and a greater comfort for the users in scenarios of application such as dwellings, offices, commercial establishments, computer centres or ensembles thereof grouped under a single building or complexes of buildings. The energy meters remain in any case the fundamental ones in the monitoring method and apparatus that is described herein.

According to a peculiar characteristic of the present invention, the above multi-sensor nodes are organized in a multilevel w i r e 1 e s ssensornetwork architecture located/distributed in a mesh (multi-hop) topology. These nodes communicate via radio forwarding the data gathered and pre-processed locally to a localized co-ordinator and control system. In part, partially processed data can be shared between the network nodes for service operations such as distributed recalibration operations. The control and co-ordination node co-ordinates and processes the information coming from the various multisensor modules both to define profiles of energy consumption of the monitored premises and for supporting actions of active control of the energy-consuming systems in order to rationalize consumption.

The integration of heterogeneous sensors on a single node and mesh topology are innovative architectural elements of the sensor network proposed. Sensor-network architectures currently available for monitoring energy consumption in buildings comprise in fact nodes constituted exclusively by energy-absorption meters. Said nodes, connected to the energy-consuming systems present in the various premises of a building, enable acquisition of data on electrical consumptions on the basis of which, via purposely configured control systems, energy-consumption profiles are processed for each type of energy-consuming systems, of users, and locations .

The advantages that the proposed multisensornode architecture affords as compared with those already available are significant:

(1) in residential and non-residential buildings, the possibility of monitoring, not only electrical consumption, but also environmental variables (temperature and humidity) and above all the presence of chemical species such as volatile organic compounds, enables an efficient control of ventilation and air- conditioning systems and consequently an energy saving;

(2) in computer centres, the possibility of monitoring, not only electrical consumption, but also the environmental variables, enables an efficient control of the air flows. Moreover, as compared to the applications available for achieving energy efficiency in computer centres based upon measure-and-management approaches , the architecture proposed enables pervasive and continuous distributed monitoring of the aforesaid variables.

The multilevel architecture of the system proposed expresses itself in the capacity for intelligence of the sensor network through a first computational level, implemented on board the sensor node. It enables local evaluations to be made of the quantities of interest (for instance: quality of the air, local energy- consumption profiles, environmental variables) by means of pattern-recognition statistical techniques. Said evaluations have proven particularly useful when the phenomena to be monitored are complex or the sensor response is affected by the presence of interfering phenomena. For example, the presence of volatile particles can jeopardize the capacity of the solid- state sensors to detect in a specific way a given target analyte. The on-board intelligence of the sensors moreover affords the further advantage of selecting the packets to be sent through the network on the basis of the significance of the values detected. In this way, a further significant enhancement in energy efficiency is obtained above all in the case where the network installed is battery-supplied. In addition, the information of high semantic level available on each individual node can be shared between the nodes to implement actions of operative control such as, for example, operations of distributed continuous calibration or actions aimed at safety of the network or of the premises in which the nodes are immersed. As regards the nodes, the capacity for responding at least partially to a safety hazard (presence of high amounts of toxic, flammable, explosive gases, etc.) may be maintained even in the case of loss of connectivity with the data-sink node.

The second computational level is necessary for co-ordinator, control and management of the information coming from all the network nodes in order to reconstruct the global state of the monitored environment by means of sensor-fusion techniques. With the aid of appropriate modelling, the processed information thus assumes semantic value and can be used for active control of the energy-consuming systems present in the building, guaranteeing a rational and efficient use of energy. For example, reconstructing the olfactive image of premises starting from the point data detected by the chemical sensors present in the network installed, it is possible to obtain a global evaluation of the air quality of the monitored premises and to decide on the eventual activation of the ventilation and/or air-conditioning systems. Another example is the possibility of carrying out actions of control aimed at shaping the demand for electrical energy by implementing distributed demand- shaping algorithms.

Unlike the monitoring system forming the subject of the invention, the systems available today for monitoring energy consumption in buildings are based on so-called dummy current sensors. These are generally organized in a wireless sensor network and acquire the data on electrical consumption of the systems to which they are connected and send via radio the data to localized control systems, where they are processed and analysed .

Further characteristics and advantages of the invention will emerge clearly from the ensuing description with reference to the attached plates of drawings, which illustrate by way of non-limiting example a preferred embodiment thereof. In the plates of drawings:

- Figures 1 and 1A illustrate, respectively, the embodiment of a monitoring system for achieving energy efficiency in a dwelling and in a computer centre according to the present invention;

- Figure 2 is a diagram of logic architecture of the embodiment of the system forming the subject of the invention for a residential or tertiary structure constituted by a number of buildings;

- Figure 3 is a detailed diagram of the logic architecture of the co-ordinator and control component of the system forming the subject of the invention; and

- Figure 4 is a detailed diagram of the logic architecture of the smart wireless sensor network of the system forming the subject of the invention.

DETAILED DESCRIPTION OF THE INVENTION

As may be seen in Figure 2, the monitoring system for achieving energy efficiency of said buildings according to the invention, comprises a multilevel architecture, the first level of which is constituted by a wireless intelligent sensor network ISN with multisensor nodes that enable acquisition of information on the current state of the various premises of a building and of the energy-consuming systems operating therein.

In particular, according to the operating context identified, physical quantities (such as electrical consumption, temperature, luminosity, presence, etc.) and chemical quantities (mainly relative humidity and volatile organic compounds) are monitored.

The second architectural level consists in a localized co-ordinator and control system CCL configured for gathering, co-ordinating, and processing the information coming from the multisensor modules installed in the various premises of a building in order to delineate profiles of energy consumption in buildings and supporting actions for active control of the energy-consuming systems operating therein.

It is to be noted that, according to the context of application, the co-ordination and control functions can be performed at the level of building as in the case described or at the level of individual dwelling/operating unit (for example, an apartment, the offices of a firm, the laboratories of a research centre, etc.) . In addition, said functions can also be replicated at a higher level C for scenarios of application comprising a number of buildings (such as the one described) or a number of dwellings/operating units .

The highest levels of the architecture proposed moreover interact with the external environment, i.e., with social-network platforms SN and external-feeding platforms EF (Meteorological Service, Energy Service, etc.) in order to acquire information (such as electricity costs, weather forecast, etc.) necessary both for processing strategies of efficient control of the energy-consuming systems of the building and for motivating the user, through sharing and comparison with the community, to pursue virtuous practices and behaviour oriented at energy saving.

Described in what follows are the architectures of the individual logic components of the system forming the subject of the invention, with reference to the attached figures, in which the embodiment illustrated regards a residential structure constituted by a number of buildings (for example, a campus, a research centre, a firm, etc . ) .

Smart-sensor network

The wireless intelligent sensor network ISN that constitutes the system proposed is made up of smart multisensor nodes, designated as a whole by 10, distributed in a mesh (multi-hop) topology, respectively, in a dwelling (Figure 1) and in a computer centre (Figure 1A) .

On the basis of the functions attributed to the system, the architecture of the nodes has been designed for providing systems comprising:

clamp-type energy-absorption meters or ones that can be integrated in electric sockets through which it is possible to acquire data on electrical consumptions of the energy-consuming systems that operate in the various premises of a building;

- electronic noses of small dimensions with on-board intelligence that enable local estimation of the concentration of pollutants in the air and, co^¬ operating with one another, reconstruction of an olfactive image of the premises in which they operate ;

- multisensor devices, which integrate energy meters and sensors of environmental variables, such as temperature and humidity specifically defined for evaluating the indices of energy efficiency in the computer centres;

- movement sensors, which detect the position of people in the premises. The architecture of each multisensor node (Figure 4) comprises a base module 4A and a data-sink module (designed to receive data) 4B configured for gathering, pre-processing, and transmitting the data acquired by the aforesaid physical devices.

The base module integrates a data- acquisition/processing platform DAQ and a data- transmitting/receiving platform Tx/Rx. In its minimal requirements, the base module must enable real-time execution of the support modules RTS for process scheduling, network formation and routing of data, and of the application-oriented modules for smart local processing of the data Cintl via pattern-recognition techniques (for example, neural networks) .

For implementing de 1 ayed-transmission or data- integration policies, capacities for local storage of the data of the order of hundreds of kilobytes are necessary. The throughput requirements in the applications of the proposed system are currently in the range of hundreds of kilobytes per second. The range, according to the applications, must support internode distances of up to tens of metres in an indoor environment.

The data-sink module consists of a base module appropriately modified for direct interfacing with a personal computer as receiver and transmitter module from and to the network of sensor nodes. This module reflects the architecture of the base module without the need to house sensors and corresponding conditioning subsystems.

The multisensor nodes of the architecture of the system proposed are provided with o n-board intelligence; i.e., they are able to evaluate locally the physical/chemical quantities detected (energy consumption, quality of the air and environmental variables, etc.) by means of pattern-recognition statistical techniques and to select the packets to be sent through the network on the basis of their significance. The intelligence implemented on board the multisensor node represents the first level of computational-intelligence of the proposed monitoring system by means of which it becomes possible to monitor even complex phenomena and manage possible interfering phenomena .

The wireless sensor network architecture proposed is based upon low-consumption wireless communication protocols such as, but not exclusively, ZigBee, which enable convenient reconfiguration of the parameters and of the network topology.

In a preferred embodiment, a wireless multisensor node of the system architecture described comprises a power source (PS), such as batteries, mains supply, or photovoltaic cells, a unit for acquisition (sensing element) of the physico-chemical quantities of interest, i.e., an array of sensors (chemical and/or physical sensors) , electronic conditioning circuits, a data-processing unit, i.e., a microcontroller and a communication interface, constituted by receiver and transmitter devices.

Assigned to the microcontroller are the implementation of the runtime supporting functions and functions of a specifically applicational nature; forming part of the latter are the data-acquisition routines, routines for management of communication protocols, and functions of smart processing of the data with computational-intelligence algorithms.

Co-ordinator and control system

The information acquired and pre-processed at the first level of the architecture proposed is transmitted via wireless or wired communication protocols to the second level of the architecture, namely, the localized co-ordinator and control system CCL (Figure 3) .

The logic architecture of the system CCL comprises modules 3A for processing and filing the information coming from all the sensor nodes distributed in the various premises of a building. In particular, the data-logging module enables gathering and management of the information in a purposely provided structured database; the sensor-fusion module enables reconstruction via sensor-fusion techniques/algorithms of the global state of the premises monitored, i.e., profiles of consumption of the energy-consuming systems, olfactive image of the premises, operative state of the computer centres, etc. The scenarios thus processed are then made available via the web service to client control applications 3B and/or monitoring applications 3C. Said client applications enable display, via purposely provided interfaces, of the information processed, sharing thereof on social- network platforms, and processing of strategies of active control of the energy-consuming systems present in the building on the basis both of the information processed and of information coming from the external environment, such as weather conditions,

market costs, etc.

These applications can be implemented on hardware platforms that may differ according to the requirements and scenarios of use. In particular, reference may be made, though not exclusively, to personal computers (desktops or laptops) , tablets, or smartphones executing Microsoft or Unix-based operating systems including Android and specific software applications necessary for providing the functions described above.

It should be noted that the system CCL thus defined implements the capacities of second-level intelligence of the monitoring system proposed, which make it possible to process efficient control strategies of the energy-consuming systems present in the buildings, favour virtuous practices and behaviour by the users, and hence obtain significant energy saving .

POSSIBLE IMPLEMENTATION

The architecture of the system proposed is an open architecture so that it does not envisage a single implementation. According to the scenarios of application and to the monitoring requirements, the various components can be integrated on a single system or on different subsystems provided that the functions described are all implemented.

Described in what follows is the implementation for a preferred embodiment of the multisensor devices of the apparatus of the present invention.

The base module of the devices of the system was provided using the commercial module Crossbow TelosB. Said module uses as microcontroller subsystem the processor TIMSP4300 F1611 manufactured by Texas Instruments and is characterized by a 10-KB RAM and 48- KB program memory. The processor has a 16-bit RISC architecture and an energy consumption in the active phase of 500 μΐ/ί, whilst it enables sleep states (with re-activation in 6 μ3) with a level of consumption of 2 μΐ/ί. The MSP430 is provided with 8 ADC (analog-to- digital-converter) external ports. The F1611 also includes a 2-port, 12-bit DAC (digital-to-analog converter) module, and an SPI interface. The filing subsystem of the module TelosB makes available 128 KB of memory for storing the values obtained from the sensors. The radio transmission/reception subsystem was implemented on the basis of the programmable chip CC2420 in compliance with the standard IEEE 802.15.4 and supplies, together with functions of PHY level, a limited support to the MAC level. The radio chip is controlled by the microprocessor through the SPI port and a series of I/O lines and digital interrupts. The radio modulation can be controlled by the microcontroller for low-energy operations and maintains the level of consumption during transmission and reception within 30 μΐ/ί. The module has an inverted-F microstrip antenna at the margin of the supporting card, located at some distance from the housing for the batteries. The antenna is a dipole where the top part is bent so that it is parallel to the ground plane. Even if it does not have an exactly omnidirectional radiation pattern, the antenna can reach a range of 50 m indoor and 125 m outdoor. The module TelosB has two expansion connectors, one with ten and the other with six pins for interfacing with analog and digital sensors and actuators.

From what has been said so far, it is evident that the system forming the subject of the invention represents a step forward as compared to the state of the art of monitoring systems for achieving energy efficiency in buildings both as regards the architecture and as regards the operations described above. As has been seen, the architecture of the system includes at least four innovative elements; namely,

1. Wireless sensor networks with mesh topology

2. Heterogeneous sensors integrated on a single node

3. On-board intelligence of the sensor nodes

4. Multilevel sensor fusion.

Said elements enable an innovative approach to the control of energy efficiency in buildings based upon continuous and pervasive monitoring both of the levels of energy consumption and of the quantities (quality of the air and environmental variables, occupation of the premises) that concur in outlining the state of operation and safety of the various premises of a building, and upon active control of the energy- consuming systems operating therein.

The aforesaid architectural elements moreover enable scalability of the system proposed to different scenarios of application (dwellings, offices, commercial establishments, computer centres, or ensembles thereof located in one and the same building or complexes of buildings) and to different requirements of measurement and control. Finally, the apparatus proposed can be considered perfectly integrable in the innovative platforms that the scientific community is seeking to define and develop, based upon integration of embedded heterogeneous systems to respond to the requirements of energy efficiency and greater comfort for users in buildings. The technologies that are investigated for providing said platforms will in fact have to provide real-time measurements to ensure the integration and control functions.

The presence of levels of sensor fusion makes it possible to enrich progressively the semantics of the data gathered enabling an appropriate reconstruction of the state of the premises and of the profiles of consumption of the energy-consuming systems. The information thus obtained, which can be used by different client applications implemented on PCs (desktops or laptops), tablets, PCs, or smartphones, enables increase of the awareness on the part of users of the levels of consumption of the energy-consuming systems and definition of strategies of active control thereof, and hence makes it possible to achieve the target of rationalizing the use of energy.

The domain of application of the monitoring system proposed comprises both individual dwellings, offices, commercial establishments, computer centres and ensembles thereof organized in one or a number of buildings where it will be possible to:

acquire information both on energy consumption and on the quality of the air and the environmental variables, enabling definition of efficient strategies of rationalization of the use of energy in dwellings, offices, and computer centres;

evaluate locally on board of the devices the quantities of interest (energy consumption, environmental variables, and quality of the air) , enabling monitoring of even complex phenomena and management of possible interfering phenomena, acting locally or communicating with a node that is able to act locally with an actuator in order to restore rapidly the safety conditions, turning on, for example, a system for fast change of the air; and

provide pervasive and continuous information on the state of operation and security of the various premises of a building and on the levels of consumption of the energy-consuming systems present therein.

Claims

1) A monitoring method for achieving energy efficiency in buildings and more in general in articulated complexes of buildings, characterized in that it envisages:

distributing/locating in premises to be monitored a plurality of multisensor devices that have wireless- communication capacity, mesh-routing capacity, and onboard intelligence capacity;

organizing said smart multisensor devices in multilevel architectures of wireless sensor networks with mesh topology;

acquiring and pre-processing locally through the first-level sensor network constituted by said smart devices information on the current state of the various premises of a building and of the energy-consuming systems operating therein and optionally monitoring physical and chemical quantities locally; and

transmitting said pre-processed information to a localized co-ordinator and control system configured for gathering, co-ordinating, and processing the pre- processed information coming from all the network nodes in order to reconstruct the global state of the environment monitored continuously.

2) The monitoring method for achieving energy efficiency in buildings and more in general in articulated complexes of buildings as per the preceding claim, characterized in that according to the applicational context, the functions of co-ordinator and control can be performed at the level of individual building or at the level of individual dwelling/operating unit.

3) The monitoring method for achieving energy efficiency in buildings and more in general in articulated complexes of buildings as per Claim 1, characterized in that the highest levels of the multilevel architecture are to interact with the external environment, such as social-network platforms and external-feeding platforms (Meteorological Service, Energy Service, etc.).

4) A monitoring apparatus for achieving energy efficiency in buildings and more in general in articulated complexes of buildings, characterized by a multilevel architecture, wherein at least the first level is constituted by a wireless sensor network made up of smart multisensor nodes located/distributed according to a mesh (multi-hop) topology in premises to be monitored, for obtaining and pre-processing information on the current state of the various premises of a building and of the energy-consuming systems operating therein in order to rationalize and optimize the consumption of energy and for monitoring the safety of the environment also by means of distributed-control algorithms, whilst the second architectural level consists in a localized co- ordinator and control system configured for gathering, co-ordinating, and processing the information acquired and pre-processed coming from said multisensor nodes installed in the various premises of a building in order to delineate profiles of energy consumption in the building and support actions of active control of the energy-consuming systems operating therein; according to the applicational context, the functions of co-ordinator and control being performable at the level of individual building or at the level of individual dwelling/operating unit,

thereby obtaining the possibility of controlling energy efficiency in buildings and/or in computer centres, through pervasive and continuous distributed monitoring .

5) The monitoring apparatus as per Claim 4, characterized in that each multisensor node is constituted by a sensor or multisensor device that has wireless-communication capacity, mesh routing capacity, and on-board intelligence capacity and integrates the functions of:

clamp-type energy-absorption meters or ones integrable in electric sockets through which to acquire data on electrical consumption;

electronic noses with on-board intelligence for estimating locally the concentration of pollutants in the air and constructing an olfactive image of the environment in which they are immersed;

integrated modules constituted by energy- absorption meters and temperature and humidity sensors specific for computer centres; and

movement sensors for detecting the presence and position of persons in the premises.

6) The monitoring apparatus as per the preceding claim, characterized in that the functions of co^¬ ordinator and control are replicated at a higher level for applicational scenarios comprising a number of buildings or a number of dwellings/operating units. 7) The monitoring apparatus as per the preceding claim, characterized in that the highest levels of the multilevel architecture are designed to interact with the external environment, such as social-network platforms and external-feeding platforms

(Meteorological Service, Energy Service, etc.).

8) The monitoring apparatus according to Claims 4 onwards, characterized in that the architecture of each multisensor node comprises a base module (4A) and a data-sink module (4B) , which are configured for gathering, pre-processing, and transmitting the data acquired by the aforesaid physical devices; said base module integrating a data-acquisition/processing (DAQ) platform and a data-transmitting/receiving (Tx/Rx) platform.

9) The monitoring apparatus according to Claims 4 onwards, characterized in that said base module is designed to enable real-time execution by support modules (RTS) to carry out process scheduling, network formation, and routing of the data, and by application- oriented modules to carry out smart local processing of the data (Cintl) via techniques of pattern recognition, such as neural networks .

10) The monitoring apparatus according to Claim 8, characterized in that the data-sink module consists of a base module appropriately modified for direct interfacing to a personal computer as receiver and transmitter module from and to the network of sensor nodes and reflects the architecture of the base module without the need to house sensors and corresponding conditioning subsystems. 11) The monitoring apparatus according to the preceding claims, characterized in that the multisensor nodes of the architecture of the apparatus are equipped with on-board intelligence; i.e., they are able to evaluate locally the physical/chemical quantities detected (energy consumption, quality of the air, and environmental variables, etc.) by means of statistical techniques of pattern recognition, to share said energy information with the other nodes for actions of distributed control and maintenance of the operativenes s of the nodes themselves (e.g., network co-ordination, mutual recalibration) , and to select the packets to send through the network on the basis of their significance.

12) The monitoring apparatus according to the preceding claims, characterized in that the information acquired and pre-processed at the first level of the architecture proposed is transmitted via wireless or wired communication protocols to the second level of the architecture, i.e., to the localized co-ordinator and control system (CCL) , which comprises modules (3A) for processing and filing the information coming from all the sensor nodes distributed in the various premises of a building, the data-logging module enabling gathering and management of the information in a purposely provided structured database, whilst the sensor-fusion module enables reconstruction, via sensor-fusion te chni que s / al go r i thms , of the global state of the premises monitored, i.e., profiles of consumption of the energy-consuming systems, olfactive image of the premises, operative state of computer centres, etc., the scenarios thus processed being then made available via web services to client control applications (3B) and/or monitoring applications (3C) that enable display, via purposely provided interfaces, of the information processed, sharing thereof on social-network platforms, and processing of strategies of active control of the energy-consuming systems present in the building on the basis both of the information processed and of information coming from the external environment, such as the weather conditions, market costs of electricity, etc.