NiceHome Riva 200 24Vdc underground swing gate kit for gates up to 2.3m

-35% NiceHome Riva 200 24Vdc underground swing gate kit for gates up to 2.3m


* Fast operation  - 15 seconds to open swing gates (up to 2.3m wide and 400Kg per leaf)

Inward and outward opening.

Can be released from inside or outside during a power cut.

Environmentally-friendly automations compatible with the SoleKit solar power kit and wireless accessories line.


* To 90 degrees without acceleration and deceleration


The Riva 200 kit is recommended for inconspicuous installation and the kit includes:

2 x Riva 200M underground motors

CLB201 external control with built-in receiver

ECC05 - 2 x 4-button radio transmitters (433MHz rolling code transmission)

PH200 - 2 x adjustable safety photocells with simple Bus connection

3 x manual release keys for manual gate opening during power cuts

FL200 adjustable flashing light with built-in aerial



Technical
BlueBus Yes
IP Rating IP67
Max Gate Leaf Length 2.3m
Max Gate Weight 400Kg
Max Speed 1.25rpm
Motor Voltage 24Vdc
Solar Power Option Yes
Work Cycle 60/h

Write a review

Please login or register to review

Nice gate automation

  • : 554
  • Brand: Nice
  • Product Code: Riva 200-nice
  • Dispatched: 1-2 Working Days
Add to Wish List Compare this Product

0 reviews / Write a review

. . .

Strictly Required Cookies

These cookies are required for the website to run and cannot be switched off. Such cookie are only set in response to actions made by you such as language, currency, login session, privacy preferences. You can set your browser to block these cookies but our site may not work then.

Analytics & Statics

These cookies are usually set by our marketing and advertising partners. They may be used by them to build a profile of your interest and later show you relevant ads. If you do not allow these cookies you will not experience targeted ads for your interests.

Marketing and Retargeting

These cookies allow us to measure visitors traffic and see traffic sources by collecting information in data sets. They also help us understand which products and actions are more popular than others.