Automation of Facility Management Processes Using Machine-to-Machine Technologies

نویسندگان

  • Sudha Krishnamurthy
  • Omer Anson
  • Lior Sapir
  • Chanan Glezer
  • Mauro Rois
  • Ilana Shub
  • Kilian Schloeder
چکیده

The emergence of machine-to-machine (M2M) technologies as a business opportunity is based on the observation that there are many more machines and objects in the world than people and that an everyday object has more value when it is networked. In this paper, we describe an M2M middleware that we have developed for a facility management application. Facility management is a time and labour-intensive service industry, which can greatly benefit from the use of M2M technologies for automating business processes. The need to manage diverse facilities motivates several requirements, such as predictive maintenance, inventory management, access control, location tracking, and remote monitoring, for which an M2M solution would be useful. Our middleware includes software modules for interfacing with intelligent devices that are deployed in customer facilities to sense real-world conditions and control physical devices; communication modules for relaying data from the devices in the customer premises to a centralized data center; and service modules that analyze the data and trigger business events. We also present performance results of our middleware using our testbed and show that our middleware is capable of scalably and reliably handling concurrent events generated by different types of M2M devices, such as RFID tags, Zigbee sensors, and location tracking tags.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Error assessment in man-machine systems using the CREAM method and human-in-the-loop fault tree analysis

Background and Objectives: Despite contribution to catastrophic accidents, human errors have been generally ignored in the design of human-machine (HM) systems and the determination of the level of automation (LOA). This paper aims to develop a method to estimate the level of automation in the early stage of the design phase considering both human and machine performance. Methods: A quantita...

متن کامل

Design of Computer Integrated Manufacturing System for Irankhodro Auto Industry

Computer-integrated manufacturing (CIM), technologies are presented as solutions to manufacturing organizations, which need to perform well in all customer-related dimensions simultaneously. In the literature, CIM technologies providing such benefits as more frequent production changes, reduced inventory level, improved ability of producing complex parts with a high degree of accuracy and repea...

متن کامل

Design of Computer Integrated Manufacturing System for Irankhodro Auto Industry

Computer-integrated manufacturing (CIM), technologies are presented as solutions to manufacturing organizations, which need to perform well in all customer-related dimensions simultaneously. In the literature, CIM technologies providing such benefits as more frequent production changes, reduced inventory level, improved ability of producing complex parts with a high degree of accuracy and repea...

متن کامل

The Use of Mobile M2M Communications in E-Logistics

Logistic processes such as fleet management and tracking of assets deeply rely on Machine-to-Machine (M2M) communication services. In recent years, M2M communication is being considered as one of the most technologies that will be dominating future intelligent pervasive applications. The wide application area of mobile M2M communications includes logistics, smart metering, e-healthcare, surveil...

متن کامل

Thermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008